mirror of
https://github.com/crawlab-team/crawlab.git
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ci: Add GitHub Actions workflow for publishing MCP package
This commit is contained in:
Marvin Zhang
126
.github/workflows/publish-mcp.yml
vendored
Normal file
126
.github/workflows/publish-mcp.yml
vendored
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@@ -0,0 +1,126 @@
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name: Publish MCP Package
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on:
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push:
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branches: [main, develop]
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paths:
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- 'mcp/**'
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pull_request:
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branches: [main, develop]
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paths:
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- 'mcp/**'
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release:
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types: [created]
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workflow_dispatch:
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inputs:
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publish_tag:
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description: 'NPM tag to publish under (latest, dev, beta, alpha)'
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required: false
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default: 'dev'
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type: choice
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options:
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- latest
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- dev
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- beta
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- alpha
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jobs:
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publish:
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runs-on: ubuntu-latest
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defaults:
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run:
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working-directory: ./mcp
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Setup Node.js
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uses: actions/setup-node@v4
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with:
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node-version: '20'
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registry-url: 'https://registry.npmjs.org'
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- name: Setup pnpm
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uses: pnpm/action-setup@v4
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with:
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version: '10.12.1'
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- name: Get pnpm store directory
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shell: bash
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run: |
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echo "STORE_PATH=$(pnpm store path --silent)" >> $GITHUB_ENV
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- name: Setup pnpm cache
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uses: actions/cache@v4
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with:
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path: ${{ env.STORE_PATH }}
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key: ${{ runner.os }}-pnpm-store-${{ hashFiles('**/pnpm-lock.yaml') }}
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restore-keys: |
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${{ runner.os }}-pnpm-store-
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- name: Install dependencies
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run: pnpm install --frozen-lockfile
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- name: Lint code
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run: pnpm run lint
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- name: Run tests
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run: pnpm run test
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- name: Build package
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run: pnpm run build
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- name: Determine npm tag
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id: npm_tag
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run: |
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if [ "${{ github.event_name }}" = "release" ]; then
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if [[ "${{ github.event.release.prerelease }}" == "true" ]]; then
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echo "tag=beta" >> $GITHUB_OUTPUT
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else
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echo "tag=latest" >> $GITHUB_OUTPUT
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fi
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elif [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
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echo "tag=${{ github.event.inputs.publish_tag }}" >> $GITHUB_OUTPUT
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elif [ "${{ github.ref }}" = "refs/heads/develop" ]; then
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echo "tag=dev" >> $GITHUB_OUTPUT
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elif [ "${{ github.ref }}" = "refs/heads/main" ]; then
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echo "tag=latest" >> $GITHUB_OUTPUT
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else
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echo "tag=dev" >> $GITHUB_OUTPUT
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fi
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- name: Check if package builds correctly
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run: |
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if [ ! -f "dist/index.js" ]; then
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echo "Build failed - dist/index.js not found"
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exit 1
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fi
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- name: Publish to NPM (dry-run for PRs)
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if: github.event_name == 'pull_request'
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run: pnpm publish --dry-run --no-git-checks --tag ${{ steps.npm_tag.outputs.tag }}
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- name: Publish to NPM
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if: github.event_name == 'release' || github.event_name == 'workflow_dispatch' || (github.event_name == 'push' && (github.ref == 'refs/heads/main' || github.ref == 'refs/heads/develop'))
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run: |
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echo "Publishing with tag: ${{ steps.npm_tag.outputs.tag }}"
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pnpm publish --no-git-checks --tag ${{ steps.npm_tag.outputs.tag }}
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env:
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NODE_AUTH_TOKEN: ${{ secrets.NPM_PUBLISH_TOKEN }}
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- name: Create GitHub Release Asset
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if: github.event_name == 'release'
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run: |
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tar -czf mcp-server-crawlab-${{ github.ref_name }}.tar.gz dist/
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- name: Upload Release Asset
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if: github.event_name == 'release'
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uses: actions/upload-release-asset@v1
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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with:
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upload_url: ${{ github.event.release.upload_url }}
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asset_path: ./crawlab/mcp/mcp-server-crawlab-${{ github.ref_name }}.tar.gz
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asset_name: mcp-server-crawlab-${{ github.ref_name }}.tar.gz
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asset_content_type: application/gzip
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@@ -1,609 +0,0 @@
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import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
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import { CrawlabClient } from "../client.js";
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import { z } from "zod";
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const AI_TOOLS = {
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// LLM Provider Management
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list_llm_providers: "crawlab_list_llm_providers",
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get_llm_provider: "crawlab_get_llm_provider",
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create_llm_provider: "crawlab_create_llm_provider",
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update_llm_provider: "crawlab_update_llm_provider",
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delete_llm_provider: "crawlab_delete_llm_provider",
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// Chat Conversations
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list_conversations: "crawlab_list_conversations",
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get_conversation: "crawlab_get_conversation",
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create_conversation: "crawlab_create_conversation",
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update_conversation: "crawlab_update_conversation",
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delete_conversation: "crawlab_delete_conversation",
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get_conversation_messages: "crawlab_get_conversation_messages",
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get_chat_message: "crawlab_get_chat_message",
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// AutoProbe (AI Web Scraping)
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list_autoprobes: "crawlab_list_autoprobes",
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get_autoprobe: "crawlab_get_autoprobe",
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create_autoprobe: "crawlab_create_autoprobe",
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update_autoprobe: "crawlab_update_autoprobe",
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delete_autoprobe: "crawlab_delete_autoprobe",
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run_autoprobe_task: "crawlab_run_autoprobe_task",
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get_autoprobe_tasks: "crawlab_get_autoprobe_tasks",
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get_autoprobe_preview: "crawlab_get_autoprobe_preview",
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get_autoprobe_pattern: "crawlab_get_autoprobe_pattern",
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// AutoProbe V2
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list_autoprobes_v2: "crawlab_list_autoprobes_v2",
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get_autoprobe_v2: "crawlab_get_autoprobe_v2",
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create_autoprobe_v2: "crawlab_create_autoprobe_v2",
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update_autoprobe_v2: "crawlab_update_autoprobe_v2",
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delete_autoprobe_v2: "crawlab_delete_autoprobe_v2",
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run_autoprobe_v2_task: "crawlab_run_autoprobe_v2_task",
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get_autoprobe_v2_tasks: "crawlab_get_autoprobe_v2_tasks",
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get_autoprobe_v2_preview: "crawlab_get_autoprobe_v2_preview",
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get_autoprobe_v2_pattern: "crawlab_get_autoprobe_v2_pattern",
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get_autoprobe_v2_pattern_results: "crawlab_get_autoprobe_v2_pattern_results",
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};
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export function configureAITools(server: McpServer, client: CrawlabClient) {
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// LLM Provider Management
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server.tool(
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AI_TOOLS.list_llm_providers,
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"List all LLM providers configured in Crawlab",
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{
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page: z.number().optional().describe("Page number for pagination (default: 1)"),
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page_size: z.number().optional().describe("Number of providers per page (default: 10)"),
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filter: z.string().optional().describe("Filter providers by name or type"),
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},
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async (args) => {
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try {
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const result = await client.getLLMProviders(args);
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return {
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content: [
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{
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type: "text",
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text: JSON.stringify(result, null, 2),
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},
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],
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};
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} catch (error) {
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return {
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content: [
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{
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type: "text",
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text: `Error listing LLM providers: ${error instanceof Error ? error.message : String(error)}`,
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},
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],
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isError: true,
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};
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}
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}
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);
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server.tool(
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AI_TOOLS.get_llm_provider,
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"Get details of a specific LLM provider",
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{
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id: z.string().describe("ID of the LLM provider"),
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},
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async ({ id }) => {
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try {
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const result = await client.getLLMProvider(id);
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return {
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content: [
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{
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type: "text",
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text: JSON.stringify(result, null, 2),
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},
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],
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};
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} catch (error) {
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return {
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content: [
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{
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type: "text",
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text: `Error getting LLM provider: ${error instanceof Error ? error.message : String(error)}`,
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},
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],
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isError: true,
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};
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}
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}
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);
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server.tool(
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AI_TOOLS.create_llm_provider,
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"Create a new LLM provider configuration",
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{
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name: z.string().describe("Display name for the provider"),
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type: z.string().describe("Provider type (e.g., 'openai', 'azure-openai', 'anthropic', 'gemini')"),
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api_key: z.string().describe("API key for the provider"),
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api_base_url: z.string().optional().describe("Custom API base URL"),
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api_version: z.string().optional().describe("API version"),
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default_model: z.string().optional().describe("Default model for this provider"),
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models: z.array(z.string()).optional().describe("List of supported models"),
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deployment_name: z.string().optional().describe("Deployment name (for Azure)"),
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},
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async (args) => {
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try {
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const result = await client.createLLMProvider(args);
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return {
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content: [
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{
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type: "text",
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text: JSON.stringify(result, null, 2),
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},
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],
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};
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} catch (error) {
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return {
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content: [
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{
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type: "text",
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text: `Error creating LLM provider: ${error instanceof Error ? error.message : String(error)}`,
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},
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],
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isError: true,
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};
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}
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}
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);
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server.tool(
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AI_TOOLS.update_llm_provider,
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"Update an existing LLM provider configuration",
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{
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id: z.string().describe("ID of the LLM provider to update"),
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name: z.string().optional().describe("Display name for the provider"),
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type: z.string().optional().describe("Provider type"),
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api_key: z.string().optional().describe("API key for the provider"),
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api_base_url: z.string().optional().describe("Custom API base URL"),
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api_version: z.string().optional().describe("API version"),
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default_model: z.string().optional().describe("Default model for this provider"),
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models: z.array(z.string()).optional().describe("List of supported models"),
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||||
deployment_name: z.string().optional().describe("Deployment name (for Azure)"),
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},
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async ({ id, ...updateData }) => {
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try {
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const result = await client.updateLLMProvider(id, updateData);
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return {
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||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
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||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error updating LLM provider: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
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||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
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);
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server.tool(
|
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AI_TOOLS.delete_llm_provider,
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"Delete an LLM provider configuration",
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{
|
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id: z.string().describe("ID of the LLM provider to delete"),
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||||
},
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||||
async ({ id }) => {
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||||
try {
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||||
await client.deleteLLMProvider(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
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||||
text: `LLM provider ${id} deleted successfully`,
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error deleting LLM provider: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
// Chat Conversations
|
||||
server.tool(
|
||||
AI_TOOLS.list_conversations,
|
||||
"List all AI chat conversations",
|
||||
{
|
||||
page: z.number().optional().describe("Page number for pagination"),
|
||||
page_size: z.number().optional().describe("Number of conversations per page"),
|
||||
filter: z.string().optional().describe("Filter conversations by title or content"),
|
||||
},
|
||||
async (args) => {
|
||||
try {
|
||||
const result = await client.getConversations(args);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error listing conversations: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.get_conversation,
|
||||
"Get details of a specific conversation",
|
||||
{
|
||||
id: z.string().describe("ID of the conversation"),
|
||||
},
|
||||
async ({ id }) => {
|
||||
try {
|
||||
const result = await client.getConversation(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error getting conversation: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.get_conversation_messages,
|
||||
"Get all messages from a conversation",
|
||||
{
|
||||
id: z.string().describe("ID of the conversation"),
|
||||
},
|
||||
async ({ id }) => {
|
||||
try {
|
||||
const result = await client.getConversationMessages(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error getting conversation messages: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
// AutoProbe V2 (Latest)
|
||||
server.tool(
|
||||
AI_TOOLS.list_autoprobes_v2,
|
||||
"List all AutoProbe V2 configurations (AI-powered web scraping)",
|
||||
{
|
||||
page: z.number().optional().describe("Page number for pagination"),
|
||||
page_size: z.number().optional().describe("Number of AutoProbes per page"),
|
||||
filter: z.string().optional().describe("Filter AutoProbes by name or URL"),
|
||||
},
|
||||
async (args) => {
|
||||
try {
|
||||
const result = await client.getAutoProbesV2(args);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error listing AutoProbes V2: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.get_autoprobe_v2,
|
||||
"Get details of a specific AutoProbe V2 configuration",
|
||||
{
|
||||
id: z.string().describe("ID of the AutoProbe"),
|
||||
},
|
||||
async ({ id }) => {
|
||||
try {
|
||||
const result = await client.getAutoProbeV2(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error getting AutoProbe V2: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.create_autoprobe_v2,
|
||||
"Create a new AutoProbe V2 configuration for AI-powered web scraping",
|
||||
{
|
||||
name: z.string().describe("Name of the AutoProbe"),
|
||||
url: z.string().describe("Target URL to scrape"),
|
||||
description: z.string().optional().describe("Description of what to extract"),
|
||||
query: z.string().optional().describe("Natural language query describing the data to extract"),
|
||||
settings: z.object({}).optional().describe("Additional configuration settings"),
|
||||
},
|
||||
async (args) => {
|
||||
try {
|
||||
const result = await client.createAutoProbeV2(args);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error creating AutoProbe V2: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.run_autoprobe_v2_task,
|
||||
"Run an AutoProbe V2 scraping task",
|
||||
{
|
||||
id: z.string().describe("ID of the AutoProbe"),
|
||||
query: z.string().optional().describe("Custom query for this run"),
|
||||
view_port: z.object({}).optional().describe("Custom viewport settings"),
|
||||
},
|
||||
async ({ id, ...params }) => {
|
||||
try {
|
||||
const result = await client.runAutoProbeV2Task(id, params);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error running AutoProbe V2 task: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.get_autoprobe_v2_preview,
|
||||
"Get a preview of what an AutoProbe V2 would extract",
|
||||
{
|
||||
id: z.string().describe("ID of the AutoProbe"),
|
||||
},
|
||||
async ({ id }) => {
|
||||
try {
|
||||
const result = await client.getAutoProbeV2Preview(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error getting AutoProbe V2 preview: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.get_autoprobe_v2_pattern,
|
||||
"Get the extraction pattern for an AutoProbe V2",
|
||||
{
|
||||
id: z.string().describe("ID of the AutoProbe"),
|
||||
},
|
||||
async ({ id }) => {
|
||||
try {
|
||||
const result = await client.getAutoProbeV2Pattern(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error getting AutoProbe V2 pattern: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
// AutoProbe V1 (Legacy Support)
|
||||
server.tool(
|
||||
AI_TOOLS.list_autoprobes,
|
||||
"List all AutoProbe V1 configurations (legacy)",
|
||||
{
|
||||
page: z.number().optional().describe("Page number for pagination"),
|
||||
page_size: z.number().optional().describe("Number of AutoProbes per page"),
|
||||
filter: z.string().optional().describe("Filter AutoProbes by name or URL"),
|
||||
},
|
||||
async (args) => {
|
||||
try {
|
||||
const result = await client.getAutoProbes(args);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error listing AutoProbes V1: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.get_autoprobe,
|
||||
"Get details of a specific AutoProbe V1 configuration",
|
||||
{
|
||||
id: z.string().describe("ID of the AutoProbe"),
|
||||
},
|
||||
async ({ id }) => {
|
||||
try {
|
||||
const result = await client.getAutoProbe(id);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error getting AutoProbe V1: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
server.tool(
|
||||
AI_TOOLS.create_autoprobe,
|
||||
"Create a new AutoProbe V1 configuration (legacy)",
|
||||
{
|
||||
name: z.string().describe("Name of the AutoProbe"),
|
||||
url: z.string().describe("Target URL to scrape"),
|
||||
description: z.string().optional().describe("Description of what to extract"),
|
||||
query: z.string().optional().describe("Natural language query describing the data to extract"),
|
||||
},
|
||||
async (args) => {
|
||||
try {
|
||||
const result = await client.createAutoProbe(args);
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: JSON.stringify(result, null, 2),
|
||||
},
|
||||
],
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: `Error creating AutoProbe V1: ${error instanceof Error ? error.message : String(error)}`,
|
||||
},
|
||||
],
|
||||
isError: true,
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
}
|
||||
Reference in New Issue
Block a user