"nf-core" matching MCP servers:

Enables interaction with the Sond Core API through the Model Context Protocol. Auto-generated from the OpenAPI specification at https://core-api-lb.sond.com/api-json to provide programmatic access to Sond's services.

Generic MCP server exposing Nexusm core capabilities (memory, conversation, knowledge, feedback, context) to MCP clients via stdio and Streamable HTTP transports.

Pairs Claude Code with Google's Gemini AI for complementary code analysis, enabling intelligent routing where Claude handles local-context operations while Gemini leverages its 1M token context for distributed system debugging and long-trace analysis.

This project is based on the Knowledge Graph Memory Server from the MCP servers repository and retains its core functionality.

Implements a Multimodal Communication Protocol server for KevoDB, allowing AI agents to interact with the key-value database through a standardized API with support for core operations like get/put, scans, transactions, and batch operations.

Provides AI agents with persistent long-term memory capabilities using semantic search. Enables storing, retrieving, and searching memories through three core tools integrated with Mem0 and vector storage.

A headless local knowledge library and RAG substrate that enables LLM clients to search, retrieve chunks, and list documentation packs through read-only MCP tools.

Enables AI agents to get read-only trust verdicts on knowledge records by evaluating evidence maturity, provenance, intended use, risk level, and scope before deciding whether knowledge may be used.

An MCP server that retrieves relevant code snippets and documents to assist in generating pymilvus code, converting between ORM and client, and translating Milvus code between programming languages.

Enables autonomous multi-agent workflows to capture, preserve, and retrieve immutable transcripts and atomic memory cards through a local MCP server, providing tools for forensic search, topic mapping, and structured fact access without losing context fidelity.

Provides a SQLite-backed off-context diary for Letta agents with MCP tools for journaling and retrieval, keeping core memory uncluttered. Supports embedding summaries and FTS fallback for semantic search.

Enables AI clients to explore MCP concepts, retrieve quickstart guides, and ask questions with Redis-cached answers, supporting deployment on Cloudflare Workers and Docker.

Provides deterministic, read-only access to engineering decisions, requirements, and designs stored as Markdown in a repository, enabling agents to retrieve and follow decided context without embeddings or external services.

Enables authorized clients to invoke tenant-aware conversational assistant tools and resources over MCP, including durable conversations, agent configuration, connector policies, and PostgreSQL-backed data.

Enables MCP clients to search and ask questions about Arknights world lore through hybrid retrieval and retrieval-augmented generation, with source annotations on generated answers.

Enables AI agents to build and query a persistent knowledge graph with entities, relationships, and observations. Features a core index system that ensures critical information is always accessible across all memory operations.

A modular MCP server suite that provides core tools, long-term memory, knowledge RAG, skills registry, and external integrations for AI agents.

A basic Model Context Protocol server implementation that demonstrates core functionality including tools and resources for AI chat applications.

A local MCP server that semantically searches Markdown context files and extension context links, providing tools for context_search, context_read, and context_status.

将 pgvector 知识库检索能力封装为标准 MCP 服务器，支持 Tools、Resources 和 Prompts，使 Claude Desktop 等客户端可通过自然语言查询知识库。