Logichive

Name: Logichive
Author: Ayato-AI-for-Auto

@Ayato-AI-for-Auto

About Logichive

🛡️ Professional AI Logic Hub: Accumulate, verify, and reuse high-quality code assets via MCP. Built for kill liberation from mundane tasks likes code copy & remenber logic.

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "LogicHive": {
      "command": "docker",
      "args": [
        "run",
        "-d",
        "\\"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Logichive?

LogicHive is a high-precision knowledge extraction and logic management system that enables AI agents to accumulate, verify, and reuse code assets via the Model Context Protocol (MCP). It uses a Hybrid Deterministic Gate (Fact, Static, AI, Execution) to veto non-factual AI opinions and enforce verifiability over correctness.

How to use Logichive?

Run the LogicHive-Hub.exe (Windows) or the Docker container, then configure your MCP client (Cursor, Claude Desktop) to connect to http://localhost:10880/sse. Set at least GEMINI_API_KEY in a .env file. Use the MCP tools to search, save, retrieve, and delete logic atoms.

Key features of Logichive

Hybrid Knowledge Search: semantic and exact-match search for code patterns
Verification Quality Gate: automated testing and linting before vaulting
MCP Streamable HTTP (SSE) Integration: centralized server for concurrent clients
Project Isolation: manage logic assets across multiple namespaces
Hybrid Deterministic Gate with four verification stages

Use cases of Logichive

Accumulating verified code snippets from AI interactions for reuse
Reducing LLM input token costs by injecting precise logic atoms
Preventing technical debt through automated assertion and redundancy checks
Securing AI governance by filtering security vulnerabilities and isolating runtime tests
Preserving critical domain logic across teams to eliminate silo effects

FAQ from Logichive

What is the Hybrid Deterministic Gate?

It is a four‑stage verification pipeline (Fact 40%, Static 30%, AI 20%, Execution 10%) that rejects logic atoms failing AST analysis, code health metrics, forensic audit, or isolated runtime validation.

How does LogicHive handle heavy imports like torch or sklearn?

Use lazy imports (move heavy imports inside functions) or the mock_imports parameter in save_function to bypass the 20‑second Quality Gate timeout.

Where is my data stored?

User data (saved logic assets) is stored locally in SQLite and ChromaDB databases on your own machine; no assets are sent to external providers unless you explicitly request context.

What are the system requirements for Logichive?

You need a Windows system (native EXE) or any OS with Docker/Podman, and a Gemini API key. Optionally, you can run Ollama for local LLM inference.

Is Logichive available under a commercial license?

Yes, LogicHive is dual‑licensed under AGPL‑3.0 and a Commercial License for proprietary use, with tiers for Indie, Startup, and Enterprise.

Comments

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