Developer Tools MCP Servers

Firefly III

Enables AI assistants to manage personal finances by interacting with Firefly III instances through a Model Context Protocol (MCP) server.

SearXNG Integration

Enables privacy-focused meta-search capabilities by integrating with SearXNG.

Jira

Exposes your entire Jira instance through the Model Context Protocol (MCP) with zero configuration.

Todo

Manages tasks via WebSocket with modular command execution and tool support, designed for integration with artificial intelligence agents.

Memory Bank

Streamlines software development projects by providing structured workflow tools across various complexity levels and phases.

LocalMind

Enables local LLM chat functionality, fully compatible with the Model Context Protocol using Azure OpenAI.

Rostro

Extends language models with on-the-fly multimodal generation capabilities for images, music, and videos.

Spawn

Provides a proof-of-concept server for streaming Model Context Protocol (MCP) data via Server-Sent Events (SSE) using STDIO transport.

Redmine

Exposes Redmine data via a Model Context Protocol server using Server Side Events.

Github PR

Enhances GitHub pull request management with structured templates, rich media support, and automated checklists.

Smalltalk Validator

Validates Tonel formatted Smalltalk source code and method definitions for syntax correctness.

Cappt

Generates outlines and presentations using the Model Context Protocol.

Exi

Runs a Java application designed to interact with the Steam platform.

Hong Kong Open Data

Provides programmatic access to the official open data portal of the Hong Kong government through a Model Context Protocol (MCP) server.

Etherscan Tools

Provides Ethereum blockchain data tools via Etherscan's API for interacting with the Ethereum blockchain.

Fayeblade

Facilitates browser automation by providing a robust bridge that communicates over `stdin/stdout` using a JSON-RPC-like protocol.

Github Issue

Provides a Model Context Protocol (MCP) server with a simple notes system.

Experiments

Enables Large Language Models (LLMs) to control a Mac desktop computer via bash and AppleScript using the Model Context Protocol (MCP).

TestRail

Integrate AI assistants with TestRail to manage projects, test cases, test runs, and results.

File Context

Enables querying Large Language Models with context derived from local files.