What is the mem-agent-mcp MCP server?

firstbatchxyz/mem-agent-mcp — mem-agent mcp server AgentRank score: 52.7/100.

Is the mem-agent-mcp MCP server actively maintained?

The mem-agent-mcp MCP server was last committed 11mo ago and has 5 contributors. Issue health: 50% of issues resolved. AgentRank freshness score reflects real-time maintenance activity.

mem-agent-mcp MCP Server

Name: firstbatchxyz/mem-agent-mcp
Rating: 3.1 (1 reviews)
Author: firstbatchxyz

firstbatchxyz/mem-agent-mcp

Score: 52.7 Rank #14614 MCP Server

[![AgentRank](https://agentrank-ai.com/api/v1/badge/firstbatchxyz--mem-agent-mcp)](https://agentrank-ai.com/tool/firstbatchxyz--mem-agent-mcp/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge)

Are you the maintainer of firstbatchxyz/mem-agent-mcp? Claim this listing →

mem-agent mcp server

Add AgentRank to Claude Code Discover and compare tools like firstbatchxyz/mem-agent-mcp — your AI finds the right one automatically

Get API Access →

claude mcp add agentrank -- npx -y agentrank-mcp-server

Overview

firstbatchxyz/mem-agent-mcp is a Python MCP server licensed under Apache-2.0. mem-agent mcp server

Ranked #14614 out of 24846 indexed tools.

Ecosystem

Python Apache-2.0

Score Breakdown

Stars 15% 626

626 stars → growing community

Freshness 25% 11mo ago

Last commit 11mo ago → stale

Issue Health 25% 50%

4/8 issues closed → decent issue management

Contributors 10% 5

5 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 100

Description Brief

License Apache-2.0

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

How to Improve

Description low impact

Expand your description to 150+ characters for better discoverability

Freshness high impact

Last commit was 346 days ago — a recent commit would boost your freshness score

Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

Badge all embed codes →

Markdown

[![AgentRank](https://agentrank-ai.com/api/v1/badge/firstbatchxyz--mem-agent-mcp)](https://agentrank-ai.com/tool/firstbatchxyz--mem-agent-mcp/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge)

HTML

<a href="https://agentrank-ai.com/tool/firstbatchxyz--mem-agent-mcp/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/firstbatchxyz--mem-agent-mcp" alt="AgentRank"></a>

Embed Widget docs →

HTML

<script src="https://agentrank-ai.com/embed.js" data-tool="firstbatchxyz/mem-agent-mcp"></script>

Details

Stars: 626
Forks: 100
Open Issues: 4
Closed Issues: 4
Contributors: 5
Dependents: —
Language: Python
License: Apache-2.0
Last Commit: 11mo ago

Matched Queries

"mcp server""mcp-server"

From the README

# mem-agent-mcp

This is an MCP server for our model [driaforall/mem-agent](https://huggingface.co/driaforall/mem-agent), which can be connected to apps like Claude Desktop or Lm Studio to interact with an obsidian-like memory system.

## Supported Platforms

- macOS (Metal backend)
- Linux (with GPU, vLLM backend)

### Platform note: aarch64 (ARM64) Linux
- On ARM64 Linux, vLLM is not installed by default to avoid build failures (no stable wheels and source builds can fail).
- Installation will succeed without vLLM; you can:
  - Use the default OpenRouter/OpenAI path (no local vLLM needed), or
  - Run vLLM on a compatible x86_64 host and point the client at it (see agent/model.py create_vllm_client).

## Running Instructions

### Using a LiteLLM proxy (OpenAI-compatible)
- If you have a LiteLLM proxy running locally (e.g., on port 4000), configure the client via .env:
```
VLLM_HOST=localhost
VLLM_PORT=4000
```
- Verify connectivity:
```
curl http://localhost:4000/v1/models
```
- Then

Read full README on GitHub →