"DAF" matching MCP servers:

Persistent project context MCP server that syncs a single .faf file to all AI tool formats (Cursor, Windsurf, Cline, etc.), enabling eternal bi-sync and optimized context for AI assistants.

Provides persistent memory capabilities through Neo4j graph database integration, allowing storage and retrieval of interconnected knowledge with complex relationships between entities. Enables long-term retention and querying of information across multiple conversations through graph-based memory management.

Persistent project context in Rust. 8 MCP tools via rmcp SDK — parse, validate, score, compress, discover, and token analysis. Single binary, zero config. IANA-registered format (application/vnd.faf+yaml). One file, every AI platform.

Lets an LLM agent write memories, search them with surprise-weighted, graph-plus-lexical retrieval and time-based forgetting, and read storage statistics. Everything runs against a local SQLite database, with no vector store or third-party client required.

Persistent project context for Google Gemini. 12 MCP tools for .faf Project DNA — auto-detect your stack, validate, score, and sync across CLAUDE.md, GEMINI.md, and AGENTS.md. Python/FastMCP. IANA-registered format (application/vnd.faf+yaml). 183 tests. One file, every AI platform.

Grok asked for MCP on a URL. This is it. First MCP server built for Grok URL-based • Zero config • Just works

This server enables interaction between Neo4j databases and Claude Desktop, allowing users to execute Cypher queries, create nodes, and establish relationships in the database.

MCP server for the Trollspace API that exposes 47 type-safe tools for managing snippets, nuggets, todos, ideas, tools, repos, travel, subscriptions, and more.

Enables humans and AI agents to collaborate live on documents in a browser-based editor, with agents connecting via OAuth-enabled MCP tools for writing, commenting, memory, files, web retrieval, and backups. It can optionally integrate school drive and learning-platform access.

Enables AI clients to incrementally build and maintain a git-backed personal wiki, providing long-term memory by compiling and cross-referencing knowledge across sessions.

Enables AI clients to search a personal corpus, read relevant source passages, and answer questions with traceable evidence from imported sessions, notes, and articles.