51e0702d94
- Fix server blocking issue during semantic indexing by using FastAPI BackgroundTasks
- Add job progress tracking with real-time status updates
- Add /api/jobs and /api/jobs/{job_id} endpoints for monitoring
- Add JobsDashboard component with live progress bars and status indicators
- Add Jobs tab to MainApp for interactive monitoring
- Maintain backward compatibility with background=false option for sync mode
- Include automatic job cleanup to prevent memory leaks
380 lines
14 KiB
Python
380 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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True MCP Server for Claude Code integration.
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Wraps the Claude OS REST API as a proper MCP server with stdio transport.
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Server name is "code-forge" for backwards compatibility with existing
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memories and documentation, but it IS Claude OS.
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Usage:
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Run: ./install.sh (this will configure everything)
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Or manually add to ~/.claude/settings.json:
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{
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"mcpServers": {
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"code-forge": {
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"command": "/path/to/claude-os/venv/bin/python3",
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"args": ["/path/to/claude-os/mcp_server/claude_code_mcp.py"],
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"env": {
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"CLAUDE_OS_API": "http://localhost:8051"
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}
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}
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}
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}
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"""
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import asyncio
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import json
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import os
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import sys
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from typing import Any
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import httpx
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from mcp.server import Server
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from mcp.server.stdio import stdio_server
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from mcp.types import Tool, TextContent
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# Configuration
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API_BASE = os.environ.get("CLAUDE_OS_API", "http://localhost:8051")
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# Initialize MCP server - named "code-forge" for backwards compatibility
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server = Server("code-forge")
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def api_url(path: str) -> str:
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"""Build full API URL."""
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return f"{API_BASE}{path}"
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async def api_get(path: str) -> dict:
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"""Make GET request to API."""
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async with httpx.AsyncClient() as client:
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response = await client.get(api_url(path), timeout=30.0)
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response.raise_for_status()
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return response.json()
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async def api_post(path: str, data: dict = None) -> dict:
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"""Make POST request to API."""
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async with httpx.AsyncClient() as client:
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response = await client.post(api_url(path), json=data or {}, timeout=60.0)
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response.raise_for_status()
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return response.json()
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async def api_delete(path: str) -> dict:
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"""Make DELETE request to API."""
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async with httpx.AsyncClient() as client:
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response = await client.delete(api_url(path), timeout=30.0)
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response.raise_for_status()
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return response.json()
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@server.list_tools()
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async def list_tools() -> list[Tool]:
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"""List available Claude OS tools.
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Tool names match what templates/commands expect:
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- mcp__code-forge__search_knowledge_base
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- mcp__code-forge__list_knowledge_bases
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- mcp__code-forge__list_documents
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- etc.
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"""
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return [
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# Knowledge Base Tools
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Tool(
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name="list_knowledge_bases",
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description="List all knowledge bases in Claude OS",
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inputSchema={
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"type": "object",
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"properties": {},
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"required": []
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}
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),
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Tool(
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name="create_knowledge_base",
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description="Create a new knowledge base",
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inputSchema={
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"type": "object",
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"properties": {
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"name": {"type": "string", "description": "Name of the knowledge base"},
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"kb_type": {"type": "string", "enum": ["generic", "code", "documentation"], "default": "generic"},
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"description": {"type": "string", "description": "Description of the KB"}
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},
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"required": ["name"]
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}
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),
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Tool(
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name="search_knowledge_base",
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description="Search/query a knowledge base using RAG. Returns relevant documents and an AI-generated answer.",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base to search"},
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"query": {"type": "string", "description": "Search query"},
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"top_k": {"type": "integer", "default": 5, "description": "Number of results to return"},
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"use_hybrid": {"type": "boolean", "default": True, "description": "Use hybrid search (semantic + keyword)"}
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},
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"required": ["kb_name", "query"]
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}
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),
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Tool(
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name="get_kb_stats",
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description="Get statistics for a knowledge base (document count, chunk count, etc.)",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base"}
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},
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"required": ["kb_name"]
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}
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),
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Tool(
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name="list_documents",
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description="List all documents in a knowledge base",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base"}
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},
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"required": ["kb_name"]
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}
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),
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Tool(
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name="delete_knowledge_base",
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description="Delete a knowledge base and all its documents",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base to delete"}
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},
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"required": ["kb_name"]
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}
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),
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# Project Tools
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Tool(
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name="list_projects",
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description="List all projects registered with Claude OS",
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inputSchema={
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"type": "object",
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"properties": {},
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"required": []
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}
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),
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Tool(
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name="create_project",
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description="Create/register a new project with Claude OS",
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inputSchema={
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"type": "object",
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"properties": {
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"name": {"type": "string", "description": "Project name"},
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"path": {"type": "string", "description": "Absolute path to project directory"},
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"description": {"type": "string", "description": "Project description"}
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},
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"required": ["name", "path"]
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}
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),
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Tool(
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name="get_project",
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description="Get details for a specific project",
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inputSchema={
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"type": "object",
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"properties": {
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"project_id": {"type": "integer", "description": "Project ID"}
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},
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"required": ["project_id"]
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}
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),
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# Indexing Tools
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Tool(
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name="index_structural",
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description="Run tree-sitter structural indexing on code files. Fast indexing that extracts functions, classes, imports.",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base"},
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"path": {"type": "string", "description": "Path to directory to index"}
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},
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"required": ["kb_name", "path"]
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}
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),
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Tool(
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name="index_semantic",
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description="Run semantic embedding indexing on a knowledge base. Creates vector embeddings for similarity search. Runs in background by default - returns job_id to check progress at /api/jobs/{job_id}.",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base"},
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"project_path": {"type": "string", "description": "Path to project to index"},
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"selective": {"type": "boolean", "description": "If true, only index top 20% most important files + docs (default: true)"},
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"background": {"type": "boolean", "description": "If true, run in background (default: true). Set false to block until complete."}
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},
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"required": ["kb_name", "project_path"]
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}
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),
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# Document Management
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Tool(
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name="upload_document",
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description="Upload/save a document or memory to a knowledge base",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base"},
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"content": {"type": "string", "description": "Content to save (markdown supported)"},
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"filename": {"type": "string", "description": "Filename for the document (e.g., 'my-memory.md')"},
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"title": {"type": "string", "description": "Title for the document"},
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"tags": {"type": "array", "items": {"type": "string"}, "description": "Tags for categorization"}
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},
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"required": ["kb_name", "content", "filename"]
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}
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),
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Tool(
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name="delete_document",
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description="Delete a document from a knowledge base",
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inputSchema={
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"type": "object",
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"properties": {
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"kb_name": {"type": "string", "description": "Name of the knowledge base"},
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"filename": {"type": "string", "description": "Filename of the document to delete"}
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},
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"required": ["kb_name", "filename"]
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}
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),
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# Utility Tools
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Tool(
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name="get_ollama_models",
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description="List available Ollama models for embeddings and LLM",
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inputSchema={
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"type": "object",
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"properties": {},
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"required": []
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}
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),
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Tool(
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name="health_check",
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description="Check if Claude OS API server is running and healthy",
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inputSchema={
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"type": "object",
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"properties": {},
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"required": []
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}
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)
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]
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@server.call_tool()
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async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
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"""Execute a Claude OS tool."""
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try:
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result = await _execute_tool(name, arguments)
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return [TextContent(type="text", text=json.dumps(result, indent=2))]
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except httpx.HTTPStatusError as e:
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error_msg = f"API error: {e.response.status_code} - {e.response.text}"
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return [TextContent(type="text", text=json.dumps({"error": error_msg}))]
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except httpx.ConnectError:
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return [TextContent(type="text", text=json.dumps({
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"error": "Cannot connect to Claude OS API. Is the server running? Start with: ./start_all_services.sh"
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}))]
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except Exception as e:
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return [TextContent(type="text", text=json.dumps({"error": str(e)}))]
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async def _execute_tool(name: str, args: dict[str, Any]) -> dict:
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"""Route tool calls to appropriate API endpoints."""
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# Knowledge Base Tools
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if name == "list_knowledge_bases":
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return await api_get("/api/kb")
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elif name == "create_knowledge_base":
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return await api_post("/api/kb", {
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"name": args["name"],
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"kb_type": args.get("kb_type", "generic"),
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"description": args.get("description", "")
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})
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elif name == "search_knowledge_base":
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return await api_post(f"/api/kb/{args['kb_name']}/chat", {
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"query": args["query"],
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"top_k": args.get("top_k", 5),
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"use_hybrid": args.get("use_hybrid", True)
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})
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elif name == "get_kb_stats":
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return await api_get(f"/api/kb/{args['kb_name']}/stats")
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elif name == "list_documents":
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return await api_get(f"/api/kb/{args['kb_name']}/documents")
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elif name == "delete_knowledge_base":
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return await api_delete(f"/api/kb/{args['kb_name']}")
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# Project Tools
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elif name == "list_projects":
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return await api_get("/api/projects")
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elif name == "create_project":
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return await api_post("/api/projects", {
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"name": args["name"],
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"path": args["path"],
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"description": args.get("description", "")
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})
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elif name == "get_project":
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return await api_get(f"/api/projects/{args['project_id']}")
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# Indexing Tools
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elif name == "index_structural":
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return await api_post(f"/api/kb/{args['kb_name']}/index-structural", {
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"path": args["path"]
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})
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elif name == "index_semantic":
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return await api_post(f"/api/kb/{args['kb_name']}/index-semantic", {
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"project_path": args["project_path"],
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"selective": args.get("selective", True),
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"background": args.get("background", True)
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})
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# Document Management
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elif name == "upload_document":
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return await api_post(f"/api/kb/{args['kb_name']}/import", {
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"content": args["content"],
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"filename": args["filename"],
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"metadata": {
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"title": args.get("title", ""),
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"tags": args.get("tags", [])
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}
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})
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elif name == "delete_document":
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return await api_delete(f"/api/kb/{args['kb_name']}/documents/{args['filename']}")
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# Utility Tools
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elif name == "get_ollama_models":
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return await api_get("/api/ollama/models")
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elif name == "health_check":
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try:
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# Simple health check - list KBs should work if server is up
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result = await api_get("/api/kb")
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return {"status": "healthy", "message": "Claude OS is running", "kb_count": len(result.get("knowledge_bases", []))}
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except Exception as e:
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return {"status": "unhealthy", "error": str(e)}
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else:
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return {"error": f"Unknown tool: {name}"}
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async def main():
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"""Run the MCP server."""
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async with stdio_server() as (read_stream, write_stream):
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await server.run(read_stream, write_stream, server.create_initialization_options())
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if __name__ == "__main__":
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asyncio.run(main())
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