What is the plur MCP server?

plur-ai/plur — Shared memory for AI agents AgentRank score: 75.0/100.

Is the plur MCP server actively maintained?

The plur MCP server was last committed 1mo ago and has 12 contributors. Issue health: 48% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

plur MCP Server

Name: plur-ai/plur
Rating: 4.0 (1 reviews)
Author: plur-ai

plur-ai/plur

Score: 75.0 → 0% Rank #3127 MCP Server

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Shared memory for AI agents

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Overview

plur-ai/plur is a TypeScript tool licensed under Apache-2.0. Shared memory for AI agents Topics: agent-memory, ai-agents, ai-memory, context-engine, llm, local-first, mcp.

Ranked #3127 out of 24846 indexed tools.

Has 12 contributors.

Ecosystem

TypeScript Apache-2.0

agent-memoryai-agentsai-memorycontext-enginellmlocal-firstmcp

Score Breakdown

Stars 15% 303

303 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 48%

428/901 issues closed → many open issues

Contributors 10% 12

12 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 37

Description Brief

License Apache-2.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

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Freshness high impact

Last commit was 35 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 473 open vs 428 closed issues — triaging stale issues improves health

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Markdown

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Details

Stars: 303
Forks: 37
Open Issues: 473
Closed Issues: 428
Contributors: 12
Dependents: —
Language: TypeScript
License: Apache-2.0
Last Commit: 1mo ago

Matched Queries

topic:mcp

From the README

<p align="center">
  <a href="https://plur.ai"></a>
</p>

# PLUR — Your agents share the same memory

Persistent, **open** memory for AI agents — local-first, zero-cost, shared across MCP tools (Claude Code, Codex, Cursor, OpenCode, Hermes, OpenClaw). Your agent's memory is plain-text **engrams** you can read, correct, and delete — not weights you can't.

[plur.ai](https://plur.ai) · [Benchmark](https://plur.ai/benchmark.html) · [Engram Spec](https://plur.ai/spec.html) · [npm](https://www.npmjs.com/org/plur-ai) · [Comparisons](comparisons/)

## Benchmarks

PLUR is memory, not just retrieval — so we measure it on more than one axis, on the **full** corpus, and we publish the harness so you can reproduce every number.

**Retrieval recall — full LongMemEval-S (N=500), R@5, fully local:**

| Stack | R@5 | Notes |
|-------|-----|-------|
| BM25 only | 92.2% | no embedder — fully airgapped |
| Hybrid (BGE-small, shipping default) | 95.6% | local embedder; one-time model download |
| **+ BGE-

Read full README on GitHub →