agent-memory-engine MCP Server
uudam42/agent-memory-engine
[](https://agentrank-ai.com/tool/uudam42--agent-memory-engine/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Memory Engine is a local-first MCP server that gives coding agents persistent, evidence-backed project memory. It automatically builds a project knowledge base, retrieves relevant architecture, constraints, incidents, and source context before complex tasks, and retains verified lessons after successful work.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
uudam42/agent-memory-engine is a Python MCP server licensed under MIT. Memory Engine is a local-first MCP server that gives coding agents persistent, evidence-backed project memory. It automatically builds a project knowledge base, retrieves relevant architecture, constraints, incidents, and source context before complex tasks, and retains verified lessons after successful work.
Ranked #2972 out of 24846 indexed tools.
Ecosystem
Score Breakdown
126 stars → growing community
Last commit 1mo ago → moderate activity
3/3 issues closed → responsive maintainer
1 contributor → solo project
No dependents → no downstream usage
19 weekly installs → early adoption
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
Matched Queries
From the README
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<strong>Local-first persistent memory and project knowledge runtime for coding agents.</strong>
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<a href="https://github.com/uudam42/agent-memory-engine/actions/workflows/ci.yml">
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<a href="https://github.com/uudam42/agent-memory-engine/blob/main/LICENSE">
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<a href="README.md">English</a> | <a href="README.zh-CN.md">中文</a>
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# Agent Memory Engine
**A local-first MCP runtime that gives coding agents persistent, evidence-backed project memory and grounded project knowledge across sessions.**
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## Why it exists
Coding agents face a fundamental problem: every session starts cold.
- They forget project context between sessions.
- They repeatedly scan repositories to re-learn what modules do.
- They lose debugging lessons and historical decisions.
- Flat RAG cannot distinguish stable constraints, past incidents, architecture decisions, and raw code evidence.
- Read full README on GitHub → Get the weekly AgentRank digest
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