"Rust" matching MCP servers:

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.

Lossless archive and search for AI agent sessions (Claude Code, Codex, opencode, pi and others), exposed to agents over MCP. Local-first, written in Rust.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Hermetic memory for AI agents — one Rust binary, one SQLite file, zero network. Recall returns evidence with provenance or abstains: no code path for making things up.

Local-first persistent memory for Claude Code and OpenAI Codex CLI. A single Rust binary captures, distills, searches, and injects project memory across sessions via hooks, MCP, CLI, and localhost REST.

Local-first agent-memory MCP server with a why() tool: recall a fact together with its connected subgraph (multi-hop), so linked memories surface even when they share no words with the query. remember/recall/relate/forget/why over one fused vector + graph + columnar engine a single offline Rust binary.

Mimir is Perseus's external persistent memory backend — a lightweight Rust MCP server that stores cross-session facts so agents remember what they learned last week. Zero network calls, no API keys, just SQLite + FTS5 running alongside your workspace.

Your coding agent can read the code. It can't read the argument behind it. lema-mcp gives your agent the recorded why — and the alternatives a project already ruled out — cited to the source. For React, Kubernetes, and Rust out of the box, and for your own repo with one command.

Developer-alpha Rust stdio MCP server for a local encrypted, append-only knowledge store. Agents search and retrieve knowledge through scoped, expiring grants.

Enables programmatic control of Obsidian vaults via REST API and MCP server for automation and AI assistant integration.

MCP server for Outline knowledge base implemented on Rust as one statically linked executable file for Linux/MacOS/Windows.

Enables AI agents to read, create, update and delete any file in a mounted folder of markdown notes, patch individual headings, blocks or frontmatter keys, search by text or JsonLogic queries over frontmatter, tags and links, and stream note changes as events. Runs as a standalone container requiring no Obsidian installation and binds only to private networks such as Tailscale or WireGuard.

Enables AI agents to persist all generated deliverables as structured Markdown in a project's /.aiartefact directory, with automatic frontmatter, metadata indexing, and full-text search.

A Rust MCP stdio server for durable project-local AI notes, enabling agents to store, search, and manage verified facts, decisions, and conventions.

Zenii is a local AI backend with persistent memory, 18 tools, and 114 API routes. MCP server exposes all tools via stdio transport. * Transport: stdio * Command: zenii-mcp-server --transport stdio * Language: Rust * License: MIT

Built-in MCP server that gives AI agents direct access to an Obsidian vault for reading, writing, searching notes, and executing commands.

Generates and queries a graph representation of a codebase to identify entities and their relationships, such as function calls and inheritance. It supports multiple languages including Python, JavaScript, and Rust to help users navigate and understand complex code structures.

CodeGraph — Open-source code intelligence MCP server. Builds a semantic graph of your codebase (functions, classes, imports, call chains) and exposes it through 31 tools. Callers, callees, impact analysis, complexity metrics, unused code detection, AI context assembly, persistent memory, cross-project search. 15 languages via tree-sitter. Single Rust binary, local-first.

A Rust-based MCP server that provides long-term memory capabilities for AI agents using keyword-based storage and retrieval. It supports isolated namespaces for different users or projects, allowing LLMs to remember and recall information across sessions.

Stores and searches AI-generated knowledge about software projects, enabling Cursor to access project structures, design patterns, best practices, and technical documentation.