Grantai MCP Server

Every AI system today has the same flaw: **it guesses instead of remembers.**

Local serverstdioPython

What is the Grantai MCP server?

Connect Grantai to Claude, Cursor or any other MCP client and it stops being a tab you switch to. Every AI system today has the same flaw: it guesses instead of remembers.. The grantai mcp server is what makes that connection.

What the server does

  • Compliance — — Exact citations, not paraphrased guesses
  • Multi-Agent — — Shared memory across your AI workforce with speaker attribution
  • Cost — — Pay for answers, not for searching
  • Security — — 100% local, AES-256 encrypted, zero data egress

Available tools

The toolset is worth reading before you wire it up, because it tells you what the integration is really for:

  • grantai_infer — Query memory for relevant context
  • grantai_teach — Store content for future recall
  • grantai_learn — Import files or directories
  • grantai_health — Check server status
  • grantai_summarize — Store session summaries
  • grantai_project — Track project state
  • grantai_snippet — Store code patterns
  • grantai_git — Import git commit history
  • grantai_capture — Save conversation turns for continuity

Installation

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.

Where it fits

This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Grantai's toolset — grantai_infer, grantai_teach, grantai_learn and 6 more — is a fair guide to whether it matches your workflow. It is maintained by solonai-com; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against Grantai's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Worth knowing first

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 9 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Grantai.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Available tools

ToolWhat it does
grantai_inferQuery memory for relevant context
grantai_teachStore content for future recall
grantai_learnImport files or directories
grantai_healthCheck server status
grantai_summarizeStore session summaries
grantai_projectTrack project state
grantai_snippetStore code patterns
grantai_gitImport git commit history
grantai_captureSave conversation turns for continuity

How to install the Grantai MCP server

{
  "mcpServers": {
    "grantai": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "--pull", "always",
               "-v", "grantai-data:/data",
               "ghcr.io/solonai-com/grantai-memory:1.8.6"]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Example prompts to try

  • Use Grantai to grantai infer.
  • Use Grantai to grantai teach.
  • Use Grantai to grantai learn.

Frequently asked questions

It connects Grantai to MCP-compatible AI assistants such as Claude and Cursor, exposing 9 tools (grantai_infer, grantai_teach, grantai_learn, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Grantai directly.