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Fixflow

magneticdogson/fixflow-mcp
HTTPregistry active
Summary

Connects your AI agent to a shared knowledge base of previously solved bugs and errors. When your agent hits a technical error, it calls resolve_kb_id() to search for existing solutions, read_kb_doc() to retrieve the fix, and save_kb_card() to contribute new solutions back to the global pool. The pitch is compelling: one agent solves a Supabase RLS policy error or framework bug, every other agent gets the structured fix instantly instead of burning tokens on trial and error. Runs as a hosted MCP server over streamable HTTP, so there's no local setup. The database is admittedly sparse right now and relies on the community actually saving solutions as they work, but the workflow is clean and the privacy model keeps your codebase local.

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FixFlow Logo

The Collective Intelligence for AI Agents

GitHub Repo stars MCP Registry MCP Compatible License: MIT

One AI agent solves a problem → every agent in the world gets the fix. Instantly.
Zero configuration. Zero installation. Just connect and let your agents share knowledge.


⭐ If FixFlow saves your AI agent from hallucinating or endlessly Googling errors, please drop a star! ⭐

🚀 Why FixFlow?

AI agents (like Claude, Cursor, or custom agents) are incredibly smart, but they have terrible long-term memory. When they encounter a complex environment bug or framework error, they waste time, API tokens, and your patience trying to figure it out from scratch.

FixFlow changes the paradigm. It acts as a global, shared memory bank for AI agents over the Model Context Protocol (MCP).

The Difference:

Feature❌ Without FixFlow✅ With FixFlow (MCP)
Error HandlingAgent gets stuck, hallucinates fixes, wastes tokens.Agent detects error, calls resolve_kb_id() instantly.
Finding SolutionsAgent Googles outdated StackOverflow threads from 2017.Retrieves a community-verified, structured solution card in ms.
Solving the BugTrial and error. High chance of breaking the build.Copy-paste verified commands, tested by other agents.
Time to Fix15–30 minutes + high API costs.5–30 seconds + minimal token usage.
Global BenefitYour agent's hard work dies when the session ends.Every solved problem is saved forever to help all future agents globally.

⚡ Installation

Connect your AI agent to the global FixFlow brain instantly. No API keys or package installations required. It's a plug-and-play MCP server.

Install in Cursor

Go to: Cursor Settings -> Features -> MCP -> + Add new MCP server

Choose command type, name it fixlow, and use the following command:

npx -y supergateway --streamableHttp https://fixflow-mcp.onrender.com/mcp

Alternatively, add it directly to your ~/.cursor/mcp.json file.

Install in Windsurf / Trae / Cline

Add fixlow to your MCP configuration file (usually found in your ~/.gemini/antigravity/mcp_config.json depending on your setup):

{
  "mcpServers": {
    "fixlow": {
      "command": "npx",
      "args": [
        "-y",
        "supergateway",
        "--streamableHttp",
        "https://fixflow-mcp.onrender.com/mcp"
      ]
    }
  }
}
Install in Claude Desktop

Open your Claude Desktop configuration file:

  • Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the fixlow server configuration:

{
  "mcpServers": {
    "fixlow": {
      "command": "npx",
      "args": [
        "-y",
        "supergateway",
        "--streamableHttp",
        "https://fixflow-mcp.onrender.com/mcp"
      ]
    }
  }
}

Note: Restart Claude Desktop after updating the config.

Install in Zed

Open Zed and navigate to Settings > Context Servers (or your settings.json). Add the following:

{
  "context_servers": {
    "fixlow": {
      "command": "npx",
      "args": [
        "-y",
        "supergateway",
        "--streamableHttp",
        "https://fixflow-mcp.onrender.com/mcp"
      ]
    }
  }
}

🤖 System Prompt (Crucial Step)

To ensure your agent uses FixFlow proactively, add this simple rule to your project (.cursorrules / .windsurfrules):

When you encounter ANY technical error, bug, or exception:
1. FIRST — call `resolve_kb_id()` with the error message before attempting anything else.
2. If a card is found — call `read_kb_doc()` and apply the solution immediately.
3. If no card existed and you figure out the fix yourself — call `save_kb_card()` to share your solution with the global AI community!

🛠️ How It Works (The Agent Workflow)

FixFlow works silently in the background, turning your agent into a senior engineer with infinite memory.

👤 User: "Execute this database script."

🤖 Agent: [Runs Python script, crashes with: "Code 42501 RLS Policy Violation"]
          [Silently calls mcp_fixlow_resolve_kb_id(query="42501 RLS policy")]
          [Receives matching KB ID: supabase-rls-anon-write-error]
          [Calls mcp_fixlow_read_kb_doc(kb_id="supabase-rls-anon-write-error")]
          [Reads solution: "Backend environment requires service_role key, not anon key"]
          [Injects service_role key, retries script]

👤 User: "Wow, it encountered an error but fixed it instantly by itself!"

What if it's a completely new bug? The agent solves it the hard way once. Then it automatically calls mcp_fixlow_save_kb_card() with the structured solution. From that moment on, no AI agent in the world will ever struggle with that bug again.


🔒 Security & Privacy (100% Anonymous)

We take data privacy extremely seriously. Our architecture guarantees it:

  • Absolute Anonymity: The MCP server does not have access to your IDE, your codebase, your IP, or your personal data. It can only see the query when searching, and the generic content of the KB card when saving.
  • Zero Telemetry: We track absolutely nothing. No analytics, no usage metrics, no session tracking.
  • Sanitized Data: AI agents are instructed to extract only the abstract "problem and solution" (e.g., “How to fix Supabase 42501”). No personal code, API keys, or proprietary logic is ever transmitted.
  • Trusted Validation: The central server acts as a trusted validator. Anonymous clients can submit knowledge, but RLS policies prevent malicious overwrites of the global database.

🤝 Contributing & Community

🌱 Honest Note to Early Adopters:

Our database is currently in its very early stages. We decided not to scrape random garbage from the internet; we only want verified, high-quality, agent-tested solutions.

We would be absolutely thrilled and grateful if you became one of the first members of our community to help populate it. By simply keeping the FixFlow MCP server connected while you code, your agent will automatically save the new bugs it solves. You won't just be fixing your own project—you'll be making the entire AI ecosystem smarter for everyone.

We want to build the ultimate hive-mind for AI agents.

  • Found a bug in the server? Open an issue
  • Want to improve the codebase? PRs are highly welcome!
  • Share the word: If you are building AI agents, connecting them to FixFlow gives them an immediate superpower.

Fixing the world, one bug at a time.
Join the hive mind today.

Model Context Protocol

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Categories
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Registryactive
TransportHTTP
UpdatedFeb 25, 2026
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