"A router for MCP (Model Context Protocol) tools" matching MCP servers:

Enables agents to load instruction modules on demand from linked git repos, keeping the always-loaded AGENTS.md slim. It syncs each module's repo before reading and returns the module text with the commit it was read at.

Enables AI agents and their users to submit, route, and monitor training jobs across free-tier GPU clouds (Kaggle, Colab, Lightning, local MPS) through a local daemon that tracks quota, explains routing decisions, and gates long or secret-reading agent jobs behind human approval.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

keeps the rules, decisions, and proof-of-work an agent needs in front of it

Enables an AI agent to host a shared folder or join an invite link as a participant in a collaborative editing session, reading, editing, and writing the files the room shares. Runs the same sync engine and wire protocol as editor clients, so an agent and a person or another agent converge on the same documents and see each other's changes.

An MCP server that exposes tools for sub-agent style reasoning across multiple LLM providers, enabling delegation of prompts to various models and running critique loops, debates, red-teaming, and answer ranking.

Search and resolve MCP server packages on the mpak registry, enabling agents to discover servers, inspect tools, and check credential requirements before installation.

Enables LLMs to access a user's personal writing context—voice, style, opinions, expertise, projects, and communication patterns—via curated markdown files, helping the LLM match the user's voice when generating written content.

Enables users to scan Hugging Face for Apple-MLX models, estimate memory fit and decode speed for their Mac, and get ranked recommendations for a use case, with all agent work running locally.

A system for defining, composing, and managing task-specific contexts for AI-powered development, enabling consistent, high-quality results.

A comprehensive Model Context Protocol server providing access to 70+ IT tools for developers and system administrators, including encoding/decoding, text manipulation, hashing, and network utilities.

Runs a task through 3 parallel AI models (China or USA preset) and returns concise responses for Claude to synthesize.

Provides deterministic intent routing and safety gating for multi-agent systems, enforcing P0 critical word detection, mutually exclusive hard rules (MX-1/2/3), and a permission matrix as pure functions via four MCP tools.

Universal work attestation for autonomous agents. Register any AI agent or machine with persistent cryptographic identity, attest completed work with tamper-evident on-chain records, and query trust scores. The reputation layer for the agent economy. 3 MCP tools over SSE. Settled on Solana.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables assistants to read-only explore and analyze Grafana dashboards and data sources, execute queries against Prometheus and Azure Log Analytics, and run guided investigation workflows.

A lightweight MCP server providing common utility tools such as unit conversion, password generation, date calculation, hashing, Base64 encoding/decoding, UUID generation, text case conversion, and text statistics, with no external dependencies.

Enables inspecting local OpenAPI specification files by listing and retrieving spec details with filters and $ref resolution.

Context+ is a semantic intelligence server that transforms codebases into searchable, hierarchical feature graphs using RAG, Tree-sitter AST, and spectral clustering. It provides tools for deep code discovery, blast radius analysis, and memory graph management for high-accuracy engineering tasks.

Provides access to ancient text corpora via stdio, enabling corpus listing, status checks, searching, and text/metadata retrieval with provenance envelopes.

Provides Chinese cultural and public data as MCP tools, including random classical poems, Chinese holiday and compensatory workday queries with annual summaries, and historical events for any date.

Enables natural-language interaction with Ladybug Tools for building performance simulation, 3D modeling, and data visualization, allowing agents to perform complex environmental analysis tasks without CAD software.

repo-release-tools mcp-server automates the software release process by managing version bumps, changelog generation, and releases. It streamlines repository maintenance by handling repetitive release tasks directly through your AI assistant.

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.

Exposes SQL Server and Snowflake schema metadata to AI coding agents, enabling schema search, join path discovery, and stored procedure metadata retrieval without live queries.

Search and explore a catalog of 2,000+ MCP servers — full-text search, trending, hot, categories, and side-by-side comparison — from any MCP client. A zero-dependency stdio bridge over the hosted awesome-mcp.tools endpoint.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

A Python framework that exposes developer tools through MCP, REST API, and CLI from a single shared registry, enabling AI assistants, HTTP clients, and terminal users to access the same tools.

Enables AI coding agents to discover and verify current open-source libraries and models using live GitHub activity, PyPI adoption, license checks, and hardware VRAM estimates before generating code.

Lets AI coding agents ask a Rails app about itself: 35 read-only tools answer from the schema, models, routes, controllers, views, jobs and conventions, over MCP or the command line, even when the app cannot boot.

Provides AI-callable tools for modernizing legacy applications, including stack detection, API contract extraction, SQL to Flyway conversion, and migration effort estimation.

Provides web automation utilities, including taking Camofox browser tab screenshots and saving them directly to local files.

Compress OCR-heavy PDFs into dense packed images so agents can work with long visual documents.

An MCP server for global tech intelligence gathering, offering tools for searching Chinese and English web content, GitHub trending, arXiv papers, HN, Exa, SEC filings, Juejin, Zhihu, Bilibili, and A-share financial reports, all without API keys and with direct China access.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

Provides a local SQLite-backed code context knowledge base with MCP tools for storing and querying code facts, call graphs, semantic info, evidence, and business mappings, plus versioned snapshot publishing and incremental sync.

Provides tools for file system operations and text generation using OpenAI-compatible models via the Model Context Protocol, supporting both stdio and HTTP transports.

A lightweight MCP server for reading public YouTube data, offering tools to fetch video transcripts, playlist contents, and video metadata without requiring an API key.