CodeAgent MCP
An autonomous code-reasoning agent that parses repositories using tree-sitter, indexes symbols into SQLite, and answers questions about the codebase through an agentic loop powered by Claude via OpenRouter.
README
CodeAgent MCP
An autonomous code-reasoning agent built on the Model Context Protocol (MCP). It parses your repository using tree-sitter, indexes all symbols into SQLite, and drives an agentic loop powered by Claude via OpenRouter to answer questions about your codebase.
Architecture
┌──────────────────────────────────────────────────┐
│ CLI (typer + rich) │
│ codeagent ask "what does Foo.bar() do?" │
└──────────────┬───────────────────────────────────┘
│
┌──────────────▼───────────────────────────────────┐
│ Agent Server (agent_server/) │
│ • Agentic loop — OpenRouter API (Claude) │
│ • Tool dispatch ↔ Code Server via MCP │
│ • Conversation history manager │
└──────────────┬───────────────────────────────────┘
│ MCP (stdio / SSE)
┌──────────────▼───────────────────────────────────┐
│ Code Server (code_server/) │
│ • FastMCP server │
│ • tree-sitter AST indexer → SQLite │
│ • Tools: search_symbols, find_callers, │
│ read_code, get_imports │
│ • watchdog file watcher (auto-reindex) │
└──────────────────────────────────────────────────┘
Setup Instructions
-
Clone the repository:
git clone <repo-url> && cd codeagent -
Set up virtual environment & install:
python3 -m venv .venv source .venv/bin/activate pip install -e . -
Configure environment variables:
cp .env.example .env # Open .env and set your OPENROUTER_API_KEY -
Index the repository:
codeagent index . -
Ask questions:
codeagent ask "How is the AST indexed into SQLite?"
Example Queries
- Find all functions:
codeagent ask "What functions are defined in this codebase?" - Trace function execution flow:
codeagent ask "Which components call start_watcher()?" - Explain architectural design:
codeagent ask "How does the file watching indexing system work?"
Environment Variables
| Variable | Required | Description |
|---|---|---|
OPENROUTER_API_KEY |
✅ | Your OpenRouter API key (sk-or-...) |
CODEAGENT_REPO |
optional | Default repo path (defaults to .) |
Tech Stack
| Layer | Library |
|---|---|
| LLM | openai SDK → OpenRouter (anthropic/claude-sonnet-4-5) |
| MCP | mcp (FastMCP) |
| Code parsing | tree-sitter ≥0.22 + tree-sitter-python + tree-sitter-javascript |
| Database | aiosqlite (async SQLite, no ORM) |
| File watching | watchdog |
| CLI | typer + rich |
| Testing | pytest + pytest-asyncio |
Development
# Run all tests
pytest -v
# Run only indexer tests
pytest tests/test_indexer.py -v
# Index a repo manually (Python API)
python3 -c "
import asyncio
from code_server.indexer import index_repo
asyncio.run(index_repo('/path/to/repo'))
"
Project Structure
codeagent/
├── code_server/
│ ├── indexer.py # tree-sitter AST → SQLite (Phase 1 ✅)
│ ├── tools.py # MCP tools: search_symbols, find_callers, read_code, get_imports
│ ├── server.py # FastMCP server
│ └── watcher.py # watchdog file watcher
├── agent_server/
│ ├── loop.py # agentic loop (OpenRouter + tool use)
│ └── history.py # conversation history manager
├── cli/
│ └── main.py # typer CLI
├── tests/
│ ├── test_indexer.py ✅ 6 passing
│ ├── test_tools.py
│ └── test_loop.py
├── .env.example
└── pyproject.toml
Build Phases
- [x] Phase 0 — Project scaffold,
pyproject.toml, venv, package installs - [x] Phase 1 — AST indexer (
indexer.py) - [x] Phase 2 — Code tools (
tools.py) - [x] Phase 3 — FastMCP server (
server.py) - [x] Phase 4 — Conversation history manager (
history.py) - [x] Phase 5 — Core Agentic loop (
loop.py) - [x] Phase 6 — Rich CLI (
main.py) - [x] Phase 7 — Watchdog file watcher (
watcher.py) - [x] Phase 8 — Verification & Test suite (36/36 tests passing)
- [x] Phase 9 — Complete README documentation
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.