Entroly MCP Server

Local context OS for AI agents with token optimization, receipts, memory, and verification.

Remote serverstreamable-httpPython

What is the Entroly MCP server?

Local context OS for AI agents with token optimization, receipts, memory, and verification. Exposed over MCP by the entroly mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

What it actually does

AI coding assistants have a memory limit. Hand one your whole codebase and it gets slow, expensive, and distracted — like giving someone a 500-page manual when they only needed page 47.

  • Shows its work — — a receipt for every decision: what was kept, what was left out and why, and what risk remains. Includes dependency links and source-span digests.
  • Fact-checks answers — — compares what the AI said against the evidence it was given, on your machine, without paying for a second AI call. WITNESS verifier, fully local.
  • Doesn't wreck your caching — — keeps the unchanging parts of your prompt stable so your provider's discount for repeated text still applies. Stable system/history bytes stay ahead of changing context.
  • Rescues sessions before they crash — — when a conversation grows too big, it trims recoverable output instead of letting the provider reject the request mid-task. Proxy-side compaction of tool output.
  • Can route cheap work to cheap models — — optional, and when it isn't confident it always picks the stronger model rather than gambling. Fail-closed routing; local ranking adapts from recorded outcomes, no embeddings API.

Adding it to your client

Being a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.

Configuration

You will need 4 environment variables: ANTHROPIC_BASE_URL, OPENAI_BASE_URL, GOOGLE_GEMINI_BASE_URL, OPENAI_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

When to reach for it

Plenty of planning and project tracking servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. It is maintained by juyterman1000; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Caveats

  • Your data travels to the provider's service, so the usual questions apply about what you send and what they retain.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the entroly mcp server does with a few real requests.

How to install the Entroly MCP server

{
  "mcpServers": {
    "entroly": {
      "command": "npx",
      "args": ["-y", "entroly"],
      "env": {
        "ANTHROPIC_BASE_URL": "your-value",
        "OPENAI_BASE_URL": "your-value",
        "GOOGLE_GEMINI_BASE_URL": "your-value",
        "OPENAI_API_KEY": "your-value"
      }
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Configuration

VariableDescriptionRequired
ANTHROPIC_BASE_URLEndpoint or connection string the server talks to.Yes
OPENAI_BASE_URLEndpoint or connection string the server talks to.Yes
GOOGLE_GEMINI_BASE_URLEndpoint or connection string the server talks to.Yes
OPENAI_API_KEYCredential the server authenticates with.Yes

Frequently asked questions

It connects Entroly to MCP-compatible AI assistants such as Claude and Cursor. Instead of copying data back and forth by hand, the assistant works with Entroly directly.