akm-mcp

akm-mcp

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

Category
Visit Server

README

stillyou

English | 中文

Memory tools remember what your agent did. stillyou remembers what you decided — and what actually shipped.

Your agent forgets. What remains is still you. — distill yourself, one session at a time.

Every session ends in amnesia: the deliverables, the decisions, the rejected alternatives, the methodology you settled on — gone. stillyou captures them automatically and hands them to your next session.

$ claude
> Continue the AI video tool comparison from last time

⏺ Your ledger has relevant history:
  [5802983d] video-tool-pricing-comparison@v1 (file/final, verified)
  Last conclusion: Kling wins on cost-per-second (¥66/mo ≈ 66s of video).
  Building the incremental comparison on that methodology — not re-deriving it...

A fresh session, zero re-explaining. That answer cites a ledger entry distilled from a session three weeks ago — same methodology, human-verified conclusion.

Install (30 seconds)

curl -fsSL https://raw.githubusercontent.com/An-idd/stillyou/main/install.sh | sh
~/.stillyou/bin/stillyou init        # pick a ledger location + register Claude Code hooks — done

Works with Claude Code today; Codex / ZCode / Cowork read the same ledger via MCP. Building from source needs bun: bun install && bun build --compile packages/cli/src/main.ts --outfile ~/.stillyou/bin/stillyou.

The five commands you'll actually use

stillyou search <keywords> find past conclusions, files, methodology (superseded versions hidden)
stillyou get <id> full entry + provenance: which session, from what inputs, why
stillyou verify <id> endorse what you've checked — it ranks up and never decays to zero
stillyou status ledger health: entry breakdown, stale warnings, failed-distill alerts
stillyou schedule --at 04:00 prefer one nightly batch over per-session distillation

Everything else is automatic: writes are journaled by hooks (zero LLM), sessions distill in a detached background process, and your first message each session pulls in relevant history under a hard token budget.

How it differs from what you already have

Versus The one-line boundary
Just re-running Re-runs can't buy back consistency or verified status — no model speed fixes two reports that disagree
claude-mem & memory frameworks They record the process (what happened); stillyou records the results (what remains, what superseded what, what's verified)
CLAUDE.md / platform memory Platforms remember facts about you, locked in their fence; stillyou records your outputs, in plain files you can walk away with
git stillyou's territory is git's blind spot: decision rationale, rejected alternatives, outputs that never enter a repo

Built for: solo creators, serial writers, analysts, vibe coders — anyone whose work is a series, not one-offs, and whose outputs live outside git. Not for: one-off tasks, chat-only use, heavyweight engineering teams (git + CI is their home turf).

Three promises: your data stays in plain markdown + jsonl you can grep (delete stillyou, keep everything); hooks never block or break your sessions; uncertain provenance stays blank — no guessing, ever.

Learn more

MIT © An-idd

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured