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Filesystem MCP Server

by abrarsavan123
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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

filesystem_mcp_server.py

JSON-RPC 2.0 MCP server exposing 6 file-system tools

mcp_client.py

Reusable stdio-transport MCP client with subprocess management

matching_agent.py

LangGraph agent — discovers + calls tools via MCP

tests/test_mcp_server.py

Unit tests for all JSON-RPC methods (no subprocess)

tests/test_agent.py

Integration tests with real subprocess + LangChain bridge

diagrams/workflow_diagram.md

6 Mermaid diagrams of the system

Related MCP server: Filesystem MCP Server

Setup

1. Install dependencies

pip install -r requirements.txt

2. Configure API key

cp .env.example .env
# Edit .env and set OPENROUTER_API_KEY

Get a free key at openrouter.ai/keys.

Running

Start the Resume Matching Agent

python matching_agent.py

Example 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.py

Running 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/ -v

MCP Server — Available Tools

Tool

Description

read_file(filepath)

Read PDF, DOCX, or TXT file; returns text + metadata

list_files(directory, extension?)

List files in a directory with optional filter

write_file(filepath, content)

Write text to a file (creates dirs as needed)

search_in_file(filepath, keyword)

Case-insensitive keyword search with context

watch_directory(directory, reset?)

NEW — Snapshot-diff monitoring for new/changed/deleted files

batch_process(filepaths, operation, keyword?)

NEW — Parallel multi-file processing via ThreadPoolExecutor

MCP Server — JSON-RPC Methods

Method

Description

initialize

MCP handshake; returns server capabilities

initialized

Client confirmation notification (no response)

tools/list

Resource discovery — lists all 6 tools with schemas

tools/call

Execute a named tool with arguments

resources/list

List file-system resources (resumes directory)

resources/read

Read a file resource by file:// URI

ping

Liveness check

JSON-RPC 2.0 Error Codes

Code

Name

When

-32700

Parse Error

Invalid JSON

-32600

Invalid Request

Not a valid JSON-RPC 2.0 message

-32601

Method Not Found

Unknown method or tool name

-32602

Invalid Params

Missing/wrong argument types

-32000

Tool Error

Tool execution failed

Workflow Diagrams

See diagrams/workflow_diagram.md for 6 Mermaid diagrams:

  1. System Architecture Overview

  2. LangGraph State Machine

  3. JSON-RPC 2.0 Message Flow (full sequence diagram)

  4. watch_directory Polling Flow

  5. batch_process Parallel Execution

  6. Error 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.

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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