bug_tracker_mcp

bug_tracker_mcp

A lightweight MCP server for tracking bugs and tasks across coding sessions, providing persistent SQLite-backed storage and six tools for logging, inspecting, updating, resolving, and deleting bugs.

Category
Visit Server

README

bug_tracker_mcp

Python 3.12+ FastMCP

A lean, agent-first Model Context Protocol (MCP) server for tracking bugs, tasks, and context across coding sessions. Designed to give AI agents (like Claude Desktop, Antigravity, and Cursor) zero-friction persistent memory for issues discovered during development.


Overview

When pair-programming with AI agents, bugs and technical debt are frequently discovered mid-task. Without a persistent tracker, these issues get lost when context windows reset.

bug_tracker_mcp solves this with a lightweight SQLite-backed MCP server. It provides 6 fast MCP tools allowing agents to log, inspect, update, resolve, and delete bugs across project-local (git repo root .bugtracker/bugs.db) or global system (~/.local/share/bug-tracker-mcp/bugs.db) scopes.


Architecture

The system is organized into decoupled Python modules:

  • FastMCP Server (bug_tracker_mcp.server): Defines stdio transport MCP tools using fastmcp.FastMCP. Handles argument validation, scope resolution, and converts internal exceptions to user-friendly ToolError responses.
  • Scope Resolution (bug_tracker_mcp.scope): Automatically detects local project root by walking parent directories for .git or respects explicit directory overrides. Supports two scopes:
    • local (default): <git_root>/.bugtracker/bugs.db
    • global: $XDG_DATA_HOME/bug-tracker-mcp/bugs.db (or ~/.local/share/bug-tracker-mcp/bugs.db)
  • SQLite Storage Layer (bug_tracker_mcp.storage): Manages SQLite connections with WAL journal mode, busy timeouts, auto-migrations via user_version, and full CRUD operations.
  • Pydantic Models (bug_tracker_mcp.models): Strict Pydantic models (Bug, BugSummary, BugListResponse) enforcing schema and typed responses.
  • Environment Configuration (bug_tracker_mcp.config): Reads optional environment variable overrides for custom local/global database paths.

Installation & Setup

Install and manage dependencies using uv:

# Clone repository
git clone https://github.com/realsidg/bug_tracker_mcp.git
cd bug_tracker_mcp

# Install dependencies and setup virtual environment
uv sync

Agent Configuration

Register bug-tracker-mcp with your agent workspace or desktop client.

Workspace .mcp.json

Add to .mcp.json in your workspace root:

{
  "mcpServers": {
    "bug-tracker": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/bug_tracker_mcp",
        "bug-tracker-mcp"
      ]
    }
  }
}

Claude Desktop (claude_desktop_config.json)

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "bug-tracker": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/bug_tracker_mcp",
        "bug-tracker-mcp"
      ]
    }
  }
}

Environment Variables

You can override storage locations by setting environment variables:

Variable Description Default
BUGTRACKER_LOCAL_ROOT Overrides root directory for local scope storage (.bugtracker/bugs.db created inside this path). Nearest directory containing .git (or current directory if none found).
BUGTRACKER_GLOBAL_ROOT Overrides root directory for global scope storage (bugs.db created inside this path). $XDG_DATA_HOME/bug-tracker-mcp or ~/.local/share/bug-tracker-mcp.

Tool Reference

bug_tracker_mcp exposes 6 tools to AI agents:

Tool Name Parameters Description
log_bug title (str, required)<br>description (str, optional)<br>severity (minor | major | blocking, default: minor) <br>location (str, optional)<br>tags (list[str], optional)<br>found_while (str, optional)<br>scope (local | global, default: local) Logs a new bug into storage and returns the created Bug record with auto-incremented ID.
list_bugs status (open | fixed | all, default: open)<br>severity (minor | major | blocking, optional)<br>tag (str, optional)<br>limit (int, default: 50)<br>offset (int, default: 0)<br>scope (local | global, default: local) Lists lightweight BugSummary items with filtering and pagination.
get_bug bug_id (int, required)<br>scope (local | global, default: local) Returns complete details of a specific bug by ID. Raises ToolError if not found.
update_bug bug_id (int, required)<br>title, description, severity, location, tags, found_while, status (optional)<br>scope (local | global, default: local) Updates specific attributes of an existing bug. Raises ToolError if not found.
resolve_bug bug_id (int, required)<br>resolution (str, optional)<br>scope (local | global, default: local) Marks a bug as fixed, sets optional resolution explanation, and records fixed_at timestamp. Raises ToolError if not found.
delete_bug bug_id (int, required)<br>scope (local | global, default: local) Permanently removes a bug by ID. Returns {"deleted": true, "bug_id": bug_id} or raises ToolError if not found.

Development & Testing

Run all quality checks:

# Run pytest test suite
uv run pytest

# Check code formatting and linting
uv run ruff check .
uv run ruff format --check .

# Run static type checker in strict mode
uv run mypy src

# Run pre-commit hooks
uv run pre-commit run --all-files

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured