Filesystem MCP Server
The official Model Context Protocol server for secure filesystem access — read, write, search, and navigate files from AI clients within configured directory boundaries.
The batteries-included agent harness.
By leveraging LangGraph, the application isolates runtime dependencies while maintaining low-latency execution traces across multi-step LLM operations.
Autonomous filesystem traversal, batch file restructuring, and format transformations
Event-driven command execution and script orchestration within scoped project boundaries
Integration into autonomous agent loops for continuous integration and task verification
{
"mcpServers": {
"deepagents": {
"command": "python",
"args": [
"-m",
"deepagents"
]
}
}
}
Paste into your client configuration file (e.g. ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%/Claude/claude_desktop_config.json on Windows).
Clone langchain-ai/deepagents from GitHub
Install dependencies with pip install -r requirements.txt (or uv sync)
Copy .env.example to .env and add your API keys
Run the skill server and connect your AI client via stdio or HTTP
Keeps heavy parsing and raw file structures external to the LLM. Only sanitized excerpts and structured returns are injected into agent memory turns.
Enforce explicit directory allowlists and permission scopes in client configuration to ensure autonomous tool calls never breach system boundaries.
Executes in an isolated local child process communicating strictly over JSON-RPC via stdio with explicit process timeouts.
Deepagents is an open-source automation capability designed for AI clients and autonomous agents. The batteries-included agent harness.
Follow the step-by-step installation: 1) Verify your runtime (Python 3.10+), 2) Add the configuration snippet into your AI client settings (e.g. claude_desktop_config.json), 3) Restart the client to initialize tool execution.
Deepagents is compatible with all AI tools supporting tool-calling and the Model Context Protocol (MCP), including Claude Desktop, Cursor, Claude Code CLI, Windsurf, OpenCode, and custom agent runtimes.
Deepagents executes locally with strict directory allowlists and permission scopes. Heavy parsing and raw file structures stay external to the LLM context window to prevent memory saturation and unauthorized access.
Yes, Deepagents is published under the MIT open-source license. You can inspect the source code and contribute on GitHub at https://github.com/langchain-ai/deepagents.
Explore open-source implementation code, license, and community releases.
The official Model Context Protocol server for secure filesystem access — read, write, search, and navigate files from AI clients within configured directory boundaries.
The awesome collection of OpenClaw skills. 5,400+ skills filtered and categorized from the official OpenClaw Skills Registry.🦞.
An open-source reference implementation of Langgraph for AI and LLM workflows.
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