TIMPS — The AI Coding Agent That Remembers Everything

🏆 Claude Code forgets everything when you close it. TIMPS remembers — forever.
100% free with Ollama • Open source • Runs fully local • No API keys required

Read in: English • 日本語 • Deutsch • Español • Français • हिन्दी • Português

TIMPS is a persistent memory layer for AI coding agents. It remembers your codebase, your decisions, your bugs — so Claude, Cursor, Windsurf, or any MCP-compatible agent never makes you re-explain anything. 9-layer memory. 17 intelligence tools. 30-second install. Free.

Table of Contents

• Try It Now (30 seconds)
• Features
• How It Works
• Comparison
• Use Cases
• Performance / Benchmarks
• FAQ
• Documentation
• Workflow Recipes
• Contributors
• Sponsors
• Star History
• Community
• License

Try It Now (30 seconds)

npx timps-code "what does this codebase do?"

That's it. No install, no config, no API key. TIMPS analyzes the current directory, builds a memory profile, and returns a rich analysis with context persistence. If you have Ollama running, everything is 100% free and local.

One-line install (Linux / macOS)

curl -fsSL https://raw.githubusercontent.com/Sandeeprdy1729/timps/main/install.sh | bash

CLI (after install)

npm install -g timps-code
cd your-project
timps "what does this codebase do?"

Auto-detects Ollama if running, or walks you through picking a provider:

timps --provider claude "refactor the auth module"    # Claude
timps --provider gemini "explain the architecture"    # Gemini
timps --provider ollama "quick fix"                   # Free local
timps --provider auto "analyze this codebase"        # Intelligent routing

MCP Server (Claude Code / Cursor / Windsurf)

npm install -g timps-mcp

Then add to ~/.claude.json (Claude Code), .cursor/mcp.json (Cursor), or ~/.config/windsurf/config.json (Windsurf):

{
  "mcpServers": {
    "timps": {
      "command": "timps-mcp"
    }
  }
}

VS Code Extension

Install from the marketplace or:

code --install-extension timps-ai-coding-agent

Full Server + Docker

git clone https://github.com/Sandeeprdy1729/timps
cd timps && docker compose up -d
npm install -g timps-mcp

Features

• 🧠 9-layer persistent memory — Episodic (session recall), Semantic (knowledge graph), Procedural (workflows), plus 6 advanced forge layers (ChronosForge, ResonanceForge, EchoForge, SynapseQuench, HarmonicSheafWeaver, and more). Memory survives across sessions, projects, and agent restarts.
• 🔧 17 intelligence tools — Contradiction detection, burnout prediction, relationship tracking, pattern detection, anomaly scoring, semantic search, drift detection, and more. Every tool is class-based, deterministic (zero Math.random()), and benchmarked.
• 💰 100% free with Ollama — Runs fully local. Zero API keys required. No telemetry. No cloud dependency.
• 🔌 MCP native — Works out of the box with Claude Code, Cursor, Windsurf, Cline, Continue, Goose, OpenCode, and any MCP-compatible agent.
• 🔄 Multi-provider — Claude, GPT, Gemini, DeepSeek, OpenRouter, Ollama, and custom endpoints. Intelligent auto-routing between providers.
• 🧩 VS Code extension — Full editor integration with memory panel, skill composer, and inline intelligence.
• 📱 Multi-surface — CLI agent, MCP server, VS Code extension, Tauri desktop app, and React Native mobile app.
• 🔌 Plugin system — Extend TIMPS with custom plugins. Plugin SDK included.
• 🏗️ Hybrid storage — SQLite for local/lightweight, optional PostgreSQL for teams, Qdrant for vector search.

How It Works

graph TB
    User["🧑 Developer"] --> CLI["CLI Agent timps-code"]
    User --> VSC["VS Code Extension"]
    User --> MCP["MCP Server timps-mcp"]

    CLI --> Core["Memory Core"]
    VSC --> Core
    MCP --> Core

    subgraph Core["TIMPS Memory Core"]
        L1["L1 Working Memory"]
        L2["L2 Episodic Memory"]
        L3["L3 Semantic Memory"]
        L4["L4 Procedural Memory"]
        L5["L5 ChronosForge"]
        L6["L6 ResonanceForge"]
        L7["L7 EchoForge"]
        L8["L8 SynapseQuench"]
        L9["L9 HarmonicSheafWeaver"]

        L1 --> L2 --> L3 --> L4
        L4 --> L5 --> L6 --> L7
        L7 --> L8 --> L9
    end

    Core --> Tools["17 Intelligence Tools"]
    Tools --> Storage["Hybrid Storage"]

    Storage --> SQLite["SQLite Local"]
    Storage --> PG["PostgreSQL Team"]
    Storage --> Qdrant["Qdrant Vector"]

    subgraph Providers["LLM Providers"]
        Ollama["Ollama 🌿 Free"]
        Claude
        GPT
        Gemini
        DeepSeek
    end

    Core --> Providers

When you ask TIMPS a question, the request flows through the 9-layer memory system. Each layer enriches the context: Working memory holds the immediate session, Episodic recalls past sessions, Semantic provides knowledge graph relationships, Procedural injects learned workflows, and the forge layers (5–9) handle time-series analysis, resonance matching, pattern synthesis, associative recall, and harmonic weaving. The 17 intelligence tools process the enriched context before returning a response that's grounded in everything TIMPS has learned about your codebase.

Comparison

Use Cases

• "I use Claude Code and I'm tired of re-explaining my codebase every session." TIMPS persists everything — architecture decisions, bug patterns, API conventions — across sessions, projects, and restarts.
• "I run Ollama locally and want an AI agent that doesn't phone home." TIMPS is 100% local with Ollama. Zero telemetry, zero API calls, zero cloud dependency.
• "I manage a large monorepo and my agent keeps forgetting context." TIMPS's 9-layer memory handles codebases of any size. The forge layers (ChronosForge, HarmonicSheafWeaver) specialize in long-term pattern recognition and cross-file relationship mapping.
• "I want my AI agent to learn from its mistakes." Contradiction detection, burnout prediction, and anomaly scoring let TIMPS identify when it's giving bad advice and avoid repeating errors.
• "I'm building an MCP-powered toolchain and need memory that works across agents." TIMPS is MCP-native. Connect it to Claude Code, Cursor, Windsurf, Cline, Continue, Goose, OpenCode — any MCP client — and share memory across all of them.

Performance / Benchmarks

All 17 intelligence tools are benchmarked continuously against a standardized evaluation suite. Results are tracked per-commit to prevent regression.

Run the benchmark suite locally:

npx tsx benchmark/index.ts --quick

All tools are deterministic — zero Math.random() calls in the intelligence layer.

FAQ

Does it work offline?
Yes. With Ollama, every operation runs locally with zero internet required.

What LLMs are supported?
Ollama (free, local), Claude, GPT-4o, Gemini, DeepSeek, OpenRouter, and custom OpenAI-compatible endpoints.

How is data stored?
Default is local SQLite. Optionally PostgreSQL (teams) and/or Qdrant (vector search). All storage is local-only unless you configure a remote database.

Is there a hosted version?
Not yet. TIMPS is self-hosted by design. Cloud hosting is on the roadmap.

Can I use TIMPS without Ollama?
Yes. TIMPS auto-detects available providers. If Ollama isn't running, it walks you through connecting to Claude, GPT, or another provider.

How does TIMPS compare to agentmemory?
TIMPS has 9 memory layers vs 1, 17 intelligence tools vs 0, supports 7 providers vs 3, includes a VS Code extension, mobile app, and plugin system. agentmemory is simpler and SQLite-only.

Can I contribute my own intelligence tools?
Yes. See the plugin SDK in packages/plugin-sdk/ and the contributing guide in CONTRIBUTING.md.

Is there a GUI?
Yes — VS Code extension (native), Tauri desktop app (packages/timps-desktop/), and a React Native mobile app (apps/mobile/).

Documentation

Package READMEs

Workflow Recipes

Four ready-to-use YAML workflows for Claude Code and other AI coding agents:

Contributors

Contributions of all kinds are welcome — code, docs, translations, plugins, or bug reports. See CONTRIBUTING.md to get started.

Bounty Program

We run periodic bounty contests for major features. Check Discord for active bounties!

Sponsors

TIMPS is free and open source. If you find it valuable, consider supporting development:

• GitHub Sponsors
• Ko-fi
• Buy Me a Coffee

Star History

Community

• Discord — real-time chat, help, announcements
• GitHub Discussions — Q&A, ideas, feature requests
• X/Twitter — announcements and updates

License

MIT