"Information on Rag and Memory" matching MCP servers:

On-device memory system for AI coding agents that captures commands, edits, and test results in a lossless ledger plus distilled facts, then provides selective recall over MCP with tools like remember, recall, search, and ask.

Exposes the four Ejentum cognitive harnesses (reasoning, code, anti-deception, memory) as MCP tools any agentic client can call. Drop-in scaffolding that catches LLM failure modes like sycophancy, hallucination, and reasoning shortcuts.

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

From ticket to reviewed pull request, on your own machine

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

Provides repository-scoped safe memory for AI coding agents with just-in-time verification against file changes to ensure facts remain accurate. It links memories to specific code citations and automatically marks them as stale if the underlying source code is modified or deleted.

Local-first, auditable memory for Codex, Claude Code, and MCP clients. It stores scoped user/project memory in SQLite or Postgres, serves read-only recall and inspection tools by default, and supports opt-in governed writeback with review and forget controls.

Outcome-based persistent memory for AI coding tools.

MCP bridge server for patchwork-os. Boots a stdio-HTTP bridge with MCP introspection over /mcp, supporting tools/list and the full MCP protocol over HTTP.

Gives AI coding assistants persistent memory, safety controls, and project awareness by tracking coding sessions, protecting critical files from modifications, and managing approval workflows with automatic changelog generation.

A tiny Hermes-friendly bridge that exposes oh-my-pi's CLI as MCP tools (prompt and doctor) for code generation and environment verification.

Provides a durable memory layer for coding agents like Claude Code and Codex by indexing codebases and enabling RAG queries, reducing rediscovery tokens and providing senior-engineer orientation.

Persistent, local memory for AI coding agents that learns how you work, not just what you said. Supports Claude Code, Codex CLI, Cursor, and any MCP client.

Enables delegating coding tasks to multiple AI CLI agents (Claude Code, Antigravity, Codex, Cursor) with session memory and diff inspection.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

Provides persistent, scoped memory and tooling for autonomous coding agents, letting lessons, decisions, and project knowledge accumulate across queue runs.

Enables multiple AI coding agents to collaborate on a project by coordinating tasks, file leases, and messages through a shared hub, preventing conflicts and enabling parallel development.

Exposes the Quebragalho pre-paid model gateway to MCP clients, letting coding agents like Claude Code, Codex, Cursor and OpenCode spawn separate repo-aware sub-agents that run on 17 frontier models, with background job tracking, routing tiers and persistent per-project memory.