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  1. Home
  2. 🧠 Knowledge & Memory
  3. Agent Memory MCP
Agent Memory MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 8:38:13 PM

Agent Memory MCP

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository42 GitHub StarsTotal stargazers on GitHub for the source repository (42 stars).Visit Website

Memory, docs, and repo context layer for engineering agents.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "agent-memory-mcp": {
      "url": "https://jina.ai/"
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧠 More in Knowledge & Memory

Documentation Overview

agent-memory-mcp

A memory, docs, and repo context layer for engineering agents.

agent-memory-mcp helps agents work with live engineering context, not just isolated notes. It combines typed memory, document retrieval, and repository-aware tools so Claude, Cursor, Codex, and other MCP clients can recall decisions, search runbooks, inspect project docs, and reuse operational knowledge across sessions.

It is designed for engineering workflows such as:

  • DevOps and platform operations
  • infrastructure changes and rollback planning
  • runbooks, changelogs, RFCs, and postmortems
  • project-level memory that stays attached to the repo

Who This Is For

  • teams using AI agents on real codebases, docs, and operational workflows
  • DevOps, platform, and infra engineers who need more than chat history
  • projects that want local-first memory today and a shared service path later

Why Not Just A Memory Tool

Most memory MCP servers focus on "store a note, recall a note."

agent-memory-mcp is aimed at a wider engineering context layer:

  • typed memory for decisions, facts, patterns, and working context
  • RAG indexing for project docs, changelogs, and knowledge files
  • repo/file tools for reading and searching allowed project paths
  • local SQLite storage with stdio today and HTTP/JSON-RPC when you need to share it

This makes it a better fit when the agent needs to answer questions like:

  • "Why did we disable HPA on this service?"
  • "What changed recently that could explain this regression?"
  • "Which runbook or RFC matches this incident?"

Table of Contents

  • Who This Is For
  • Why Not Just A Memory Tool
  • Features
  • What Improved For Users
  • Start Local In 3 Minutes
  • Local-Only Mode
  • Index Your Repo In 2 Commands
  • Turn It Into A Team Service Later
  • Installation Options β€” Homebrew, binary, source, Docker
  • CLI Mode
  • MCP client configuration β€” Claude Desktop, Cursor, Codex
  • Recommended Workflow Snippets β€” what to paste into CLAUDE.md / .cursorrules
  • CLI commands
  • MCP tools reference β€” and JSON examples in docs/MCP_TOOLS.md
  • Configuration β€” env vars, hot-reload, indexing safety
  • Security And Operations
  • Architecture
  • macOS service installation
  • Troubleshooting / FAQ
  • Development

Reference docs: HOOKS Β· MCP_TOOLS Β· SHARED_SERVICE Β· STEWARDSHIP Β· SEDIMENTATION Β· BACKUP_RESTORE Β· SECURITY Β· THREAT_MODEL Β· CONTRIBUTING Β· CHANGELOG

Features

  • Automatic session capture β€” Claude Code hooks auto-capture knowledge at session end, save checkpoints before context compression, and compile pending summaries at session start
  • Typed persistent memory with 4 types: episodic, semantic, procedural, working
  • Hybrid retrieval that combines embeddings with keyword/BM25-like ranking
  • RAG indexing for project docs, changelogs, and knowledge archives (enabled by default in stdio/CLI mode; disabled by default in the Homebrew service preset β€” see Installation Options)
  • Repo-aware file tools for listing, reading, and searching allowlisted paths
  • Knowledge stewardship β€” automated maintenance: duplicate detection, conflict resolution, stale detection, drift scanning, and a review inbox
  • Temporal knowledge model β€” track when knowledge was valid, build supersession chains, and query "what was true at time T"
  • Dual transport: stdio for MCP clients, HTTP/JSON-RPC for APIs and shared setups
  • SQLite storage for both memory and vector index -- no external databases needed
  • Auto-indexing with file watcher for long-running local or service mode

What Improved For Users

  • Lower memory usage: memory store now reads from SQLite directly instead of loading everything into RAM β€” large memory banks no longer risk OOM
  • Opinionated solo-local setup: one recommended layout, one data directory, one quick smoke path
  • Auto-loaded .env: run from your project root without manually sourcing environment variables
  • Local-only embedding mode: keep hosted providers disabled and send text only to your local Ollama endpoint
  • Safer semantic recall: memories from a different embedding model no longer produce misleading matches
  • Explicit migration flow: use agent-memory-mcp reembed for memory migration and agent-memory-mcp index for RAG rebuilds after switching models
  • Better visibility: stats and memory_stats show how many memories belong to each embedding model, and name the ones no semantic query can reach β€” records the encoder refused outright, and records embedded from their opening only
  • Ready MCP client configs: generate copy-paste snippets for Claude Desktop, Cursor, and Codex
  • Safer indexing defaults: built-in directory excludes, optional per-path exclude globs, and secret redaction before documents are indexed
  • Source-aware retrieval: docs, ADRs, RFCs, changelogs, runbooks, postmortems, CI configs, Helm, Terraform, and K8s files are classified and surfaced with source metadata
  • Hybrid ranking for search: semantic similarity is now combined with keyword matches, recency, and source-aware weighting instead of cosine similarity alone
  • Trust-aware retrieval: memory and document results now expose source_type, confidence, freshness, owner, and last_verified_at, and ranking uses trust/freshness instead of similarity alone
  • Explainable retrieval: opt-in debug output shows filters, score components, and applied boosts for every result
  • DevOps-first tools: store decisions, incidents, runbooks, and postmortems with domain-specific MCP tools instead of generic memory calls
  • Memory lifecycle: memories move through statuses β€” active, outdated, superseded, canonical β€” so stale knowledge gets downranked automatically instead of polluting recall
  • Manual consolidation workflow: merge duplicates, mark outdated notes, promote canonical entries, and inspect conflict groups without deleting history
  • Explicit canonical knowledge layer: list and recall confirmed knowledge separately from raw memory, and surface canonical context first in project summaries
  • Project bank views: see maintained knowledge organized by category β€” decisions, runbooks, incidents, caveats, migrations, review queue β€” instead of a flat memory list
  • Session close pipeline: when a session ends, memory is analyzed, classified, and consolidated with existing knowledge instead of blindly appended
  • Explainable consolidation: session close reports show what will be added, merged, outdated, or promoted, with a decision trace and risk level for each action
  • DevOps session modes: close-session adapts behavior based on session type β€” incident and migration sessions get stricter review-first policy, coding sessions auto-apply low-risk updates
  • Shared service packaging: a working Docker Compose recipe, shared env template, nginx reverse proxy example, and a dedicated shared deployment guide
  • Built-in retrieval console: inspect hybrid ranking, trust, and normal-vs-debug retrieval in a lightweight HTTP UI at /console
  • Safer HTTP defaults: HTTP mode binds to 127.0.0.1 by default; non-loopback binds require auth unless you explicitly opt into unsafe unauthenticated access
  • Consistent CLI and MCP behavior: memory type validation, tag normalization, query/content limits, and trust summaries now follow the same policy across both interfaces
  • Knowledge stewardship: steward_run executes a full maintenance cycle β€” duplicate detection, conflict resolution, stale entry scanning, and canonical promotion candidates β€” with a single command
  • Stewardship inbox: review-required actions from maintenance runs, drift scans, and session consolidation land in one actionable queue instead of being silently applied or lost
  • Drift detection: drift_scan compares memory entries against live repo files and docs to find stale, missing, or changed references
  • Verification model: verify_entry and verification_candidates let agents and users track when knowledge was last verified and what needs attention
  • Canonical health diagnostics: steward runs now include a health summary for canonical entries β€” stale, unverified, conflicting, and low-support
  • Policy-governed automation: stewardship thresholds, auto-apply rules, and scheduling are configurable via steward_policy and environment variables
  • Temporal knowledge: memories can carry valid_from / valid_until timestamps, and recall_as_of retrieves knowledge that was valid at a specific point in time
  • Supersession chains: mark_outdated with a superseding entry automatically builds bidirectional links (superseded_by / replaces) and sets temporal boundaries
  • Knowledge timeline: knowledge_timeline shows the chronological evolution of knowledge on a topic

Read the full README β†’View source on GitHub β†’

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Frequently Asked Questions about Agent Memory MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "agent-memory-mcp": { "command": "npx", "args": ["-y", "Agent Memory MCP"] } }

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Technical Specs & Signals

Category🧠Knowledge & Memory
More technical detailsExpand β–Ύ
TransportSSE (Remote)
RuntimeNode.js
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars42
GitHub Star CountTotal stargazers on GitHub representing community popularity (42 stars).
39Quality signal: Fair Β· 39/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools15/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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