"Persistent" matching MCP servers:

Creates and maintains a semantic knowledge graph of code that allows maintaining context across sessions with Claude, providing advanced search capabilities without requiring the entire codebase in the context window.

Enables interaction with the ACL2 theorem prover through 15 tools for theorem proving, expression evaluation, persistent session management, and proof debugging.

Enables proof-backed code audit via MCP tools for AST-based code maps, symbol lookup, callers, audit commands, and persistent verdict memory.

Provides persistent memory for coding agents and grounds their claims by verifying against the actual codebase, preventing hallucinated responses.

Analyzes codebases to produce a persistent code knowledge graph and an MCP server with 9 tools for AI coding agents.

An MCP server that provides CLI coding agents with persistent decision memory, codebase dependency-graph awareness, plan validation against architectural constraints, and a self-bootstrapping constraints.md file.

Bridges the Model Context Protocol with Language Server Protocol to provide AI agents with persistent access to code intelligence features including navigation, diagnostics, refactoring, and completion across 7+ programming languages.

Persistent memory for AI coding agents that knows when it has gone stale.

A self-hosted persistent memory platform for AI agents and humans offering tools for memory storage, search, beliefs, work management, and code intelligence via MCP.

A stateful Model Context Protocol server for interactive Agda proof development, enabling persistent sessions with goal-aware proof actions.

Provides AI coding agents with persistent architectural memory of codebases, enabling impact analysis, test generation, and code generation with reduced token usage.

Validates Mermaid diagram syntax using a persistent browser for fast, reliable checks.

Provides persistent codebase memory and semantic context for AI agents via AST-aware chunking and symbol graph indexing.

coldstart gives coding agents durable memory of a specific codebase, with no embeddings, no vector store, and no API key. Agents write notes after real tasks — what a file is for, how a flow spans files, which invariants hold — and those notes are surfaced automatically to a later session whose task matches, so nothing gets rediscovered from scratch. Every note is anchored to real files by content

Semantic codebase search + persistent working memory for AI code editors. Local, zero-config, MCP. No API key.

A technical interviewer that ingests GitHub repos, teaches you your own code, and conducts mock interviews with persistent memory of your weak spots.

MCP server for Umtri — give your AI coding agent a persistent map of your project's structure, dependencies, and bugs.

Provides AI coding assistants with persistent memory, AST-based project indexing, and tools for live context management and hallucination detection. It enables saving lessons to local files, trimming conversation history, and verifying code symbols to prevent errors.

Mason indexes your codebase into a persistent concept map linking features and flows to their implementing files, so AI agents can answer "where is X implemented" without running grep/glob. It also provides pre-edit impact analysis and generates CLAUDE.md files from structured analysis of git history, architectural file sampling, and test mappings.

Give your AI agent PDF summarization, code review, translation, web extraction, document comparison, and persistent memory — all paid autonomously via Bitcoin Lightning.