Filesystem MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Filesystem MCP ServerList all resumes in the resumes folder"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Integration Project — Resume Matching Agent
Milestone 2: Replaces direct file-system tool imports with a fully spec-compliant Model Context Protocol (MCP) server, consumed by a LangGraph agent.
Architecture
User
│
▼
matching_agent.py (LangGraph state machine)
│
│ JSON-RPC 2.0 over stdio
▼
mcp_client.py (subprocess manager + RPC transport)
│
▼
filesystem_mcp_server.py (MCP server, 6 tools)
│
▼
resumes/ (file system)Key files
File | Role |
| JSON-RPC 2.0 MCP server exposing 6 file-system tools |
| Reusable stdio-transport MCP client with subprocess management |
| LangGraph agent — discovers + calls tools via MCP |
| Unit tests for all JSON-RPC methods (no subprocess) |
| Integration tests with real subprocess + LangChain bridge |
| 6 Mermaid diagrams of the system |
Setup
1. Install dependencies
pip install -r requirements.txt2. Configure API key
cp .env.example .env
# Edit .env and set OPENROUTER_API_KEYGet a free key at openrouter.ai/keys.
Running
Start the Resume Matching Agent
python matching_agent.pyExample queries:
"List all resumes in the resumes folder""Find candidates with Python skills and rank them by experience""Batch read all resumes and create a skills comparison report""Watch the resumes folder for new candidates""Read Alice Johnson's resume and write a one-paragraph summary"
Test the MCP server standalone
# Send a raw JSON-RPC request
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"0.1"}}}' | python filesystem_mcp_server.py
# Test the MCP client
python mcp_client.pyRunning Tests
# Unit tests (fast, no subprocess)
python -m pytest tests/test_mcp_server.py -v
# Integration tests (spawns subprocess)
python -m pytest tests/test_agent.py -v -s
# All tests
python -m pytest tests/ -vMCP Server — Available Tools
Tool | Description |
| Read PDF, DOCX, or TXT file; returns text + metadata |
| List files in a directory with optional filter |
| Write text to a file (creates dirs as needed) |
| Case-insensitive keyword search with context |
| NEW — Snapshot-diff monitoring for new/changed/deleted files |
| NEW — Parallel multi-file processing via ThreadPoolExecutor |
MCP Server — JSON-RPC Methods
Method | Description |
| MCP handshake; returns server capabilities |
| Client confirmation notification (no response) |
| Resource discovery — lists all 6 tools with schemas |
| Execute a named tool with arguments |
| List file-system resources (resumes directory) |
| Read a file resource by |
| Liveness check |
JSON-RPC 2.0 Error Codes
Code | Name | When |
| Parse Error | Invalid JSON |
| Invalid Request | Not a valid JSON-RPC 2.0 message |
| Method Not Found | Unknown method or tool name |
| Invalid Params | Missing/wrong argument types |
| Tool Error | Tool execution failed |
Workflow Diagrams
See diagrams/workflow_diagram.md for 6 Mermaid diagrams:
System Architecture Overview
LangGraph State Machine
JSON-RPC 2.0 Message Flow (full sequence diagram)
watch_directoryPolling Flowbatch_processParallel ExecutionError Handling Flow
Dependency on Milestone 1
This project is a refactoring of the LLM-Powered-File-System-Assistant (Milestone 1). The 4 original tools (read_file, list_files, write_file, search_in_file) are ported into the MCP server. The direct import fs_tools in llm_file_assistant.py is replaced by the MCP protocol layer.
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