Google PageRank for AI agents. 25,000+ tools indexed.

daidocs MCP Server

Kerneta/daidocs

Score: 53.2 Rank #13943 MCP Server
[![AgentRank](https://agentrank-ai.com/api/v1/badge/Kerneta--daidocs)](https://agentrank-ai.com/tool/Kerneta--daidocs/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge)
Are you the maintainer of Kerneta/daidocs? Claim this listing →

Open plain-text file format for AI memory. Your assistant's long-term memory as .dai files on your disk: readable by Claude, GPT, Gemini, Cursor, local models and grep (all LLM models work). MCP server + hooks for Claude Code, Claude Desktop, Cursor, Windsurf, Codex. 83% LongMemEval-S (GPT-4o), 92% (Claude Fable 5), 10x fewer tokens.

Add AgentRank to Claude Code Discover and compare tools like Kerneta/daidocs — your AI finds the right one automatically
Get API Access →
claude mcp add agentrank -- npx -y agentrank-mcp-server

Overview

Kerneta/daidocs is a Python MCP server licensed under Apache-2.0. Open plain-text file format for AI memory. Your assistant's long-term memory as .dai files on your disk: readable by Claude, GPT, Gemini, Cursor, local models and grep (all LLM models work). MCP server + hooks for Claude Code, Claude Desktop, Cursor, Windsurf, Codex. 83% LongMemEval-S (GPT-4o), 92% (Claude Fable 5), 10x fewer tokens.

Ranked #13943 out of 24846 indexed tools.

Ecosystem

Python Apache-2.0

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 53

53 stars → early stage

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 0%

0/4 issues closed → many open issues

Contributors 10% 1

1 contributor → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 4
Description Detailed
License Apache-2.0

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

How to Improve

Freshness high impact

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

Issue Health high impact

You have 4 open vs 0 closed issues — triaging stale issues improves health

Contributors medium impact

Single-contributor projects carry bus-factor risk — welcoming contributors boosts confidence

Badge all embed codes →

AgentRank score for Kerneta/daidocs
[![AgentRank](https://agentrank-ai.com/api/v1/badge/Kerneta--daidocs)](https://agentrank-ai.com/tool/Kerneta--daidocs/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge)
<a href="https://agentrank-ai.com/tool/Kerneta--daidocs/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/Kerneta--daidocs" alt="AgentRank"></a>

Embed Widget docs →

Embed a rich score widget on your site or blog.

<script src="https://agentrank-ai.com/embed.js" data-tool="Kerneta/daidocs"></script>

Matched Queries

"mcp server""mcp-server"topic:mcptopic:mcp-server

Get the weekly AgentRank digest

Top movers, new tools, ecosystem insights — straight to your inbox.