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okf-agent-memory MCP Server

okf-memory/okf-agent-memory

Score: 86.7 ↓ 1.7% Rank #639 Database
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Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

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Overview

okf-memory/okf-agent-memory is a Go MCP server licensed under MIT. Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go. Topics: agent-memory, ai-agents, bm25, coding-agents, developer-tools, git-native, go, golang, knowledge-base, knowledge-graph, llm-memory, markdown, mcp, mcp-server, model-context-protocol, okf, open-knowledge-format, persistent-memory.

Ranked #639 out of 24849 indexed tools.

In the top 3% of all indexed tools.

Actively maintained with commits in the last week.

Ecosystem

Go MIT
agent-memoryai-agentsbm25coding-agentsdeveloper-toolsgit-nativegogolangknowledge-baseknowledge-graphllm-memorymarkdownmcpmcp-servermodel-context-protocolokfopen-knowledge-formatpersistent-memory

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 757

757 stars → growing community

Freshness 25% 2d ago

Last commit 2d ago → actively maintained

Issue Health 25% 73%

11/15 issues closed → decent issue management

Contributors 10% 6

6 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 59
Description Detailed
License MIT

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

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Matched Queries

"mcp server""mcp-server"topic:mcptopic:mcp-servertopic:model-context-protocol

From the README

# OKF Agent Memory

> **A Domain-Neutral, Git-Native Persistent Project Memory for AI Agents based on the Open Knowledge Format (OKF) v0.2.**

---

## 🌟 Overview

Conversations with AI agents reset when context windows close. Valuable architectural decisions, domain discoveries, and operational facts are lost unless stored persistently.

Traditional approaches suffer from two fatal failure modes:
1. **The Prompt Monolith**: Stuffing all domain knowledge and rules into `AGENTS.md` or `CLAUDE.md` creates massive context bloat and causes **attention drift** (agents ignore critical instructions).
2. **The RAG Blindspot**: Dumping behavioral rules into vector databases fails because agents never semantically search for operational constraints (e.g. formatting or security rules) during general tasks.

**OKF Agent Memory** resolves this dilemma with the **Dual-Memory Agent Architecture (DMAA)**:

```mermaid
flowchart TD
    subgraph PUSH["1. Normative Working Memory (Push Layer)"]
        di
Read full README on GitHub →

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