anvaiops-mcp

Give any AI agent operational memory. An MCP server that connects Claude (Desktop, Code), and any other MCP client, to AnvaiOps — the memory layer for AI agents and the teams they work with.

Agents search past incidents, fixes, and decisions with provenance (source, team, resolution time, RCA), and persist what they learn back into shared memory.

"Your next answer may already exist."

Verified end-to-end

Every claim on this page is backed by a reproducible session: demo/transcript.md shows a real agent search (31 ms, provenance included), a memory write, and a later session finding that agent-written memory ranked #1. demo/e2e.js re-runs the whole chain with PASS/FAIL assertions — npm run demo:e2e against any deployment.

Related MCP server: mem0-mcp-selfhosted

Tools

Status labels follow the AnvaiOps ADR-0014 discipline — no tool claims more than it delivers.

Install

Works today straight from GitHub (the prepare script builds on first use; npm package pending):

"command": "npx", "args": ["-y", "github:anvai-labs/anvaiops-mcp"]

Claude Desktop

Add to claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "anvaiops": {
      "command": "npx",
      "args": ["-y", "anvaiops-mcp"],
      "env": {
        "ANVAIOPS_API_KEY": "your-key",
        "ANVAIOPS_URL": "https://anvaiops.com"
      }
    }
  }
}

Claude Code

claude mcp add anvaiops -- npx -y anvaiops-mcp
export ANVAIOPS_API_KEY=your-key   # or put it in the server env

Self-hosted

Point at your own deployment (the same server works against any AnvaiOps install):

{ "ANVAIOPS_URL": "http://localhost:8000", "ANVAIOPS_API_KEY": "local-key" }

Configuration

Get a hosted key from the AnvaiOps console — or run your own; the memory core is open source on ProximaDB.

Why an MCP server for memory?

Every team deploying agents rediscovers the same wall: retrieval is getting cheap, but re-deriving what the organization already knew never gets cheap. The same incident gets debugged three times because the answer lives in a Slack thread from March.

AnvaiOps indexes tickets, Slack threads, runbooks, post-mortems, and release notes — then surfaces the historical fix, with provenance, the moment it's relevant. This server makes that memory available to any agent, in the tool layer, where agents already work.

Design notes:

• Provenance is not optional. Every search result carries its source, team, and timestamps — a memory without provenance is a liability.

• Writes are attributed and bounded. 1–25 records per call, async ingest, tagged recorded_by — so agent-written memory stays auditable.

• Zero runtime dependencies. Hand-rolled MCP stdio (JSON-RPC 2.0, protocol 2024-11-05 → 2025-06-18), global fetch. Small supply-chain surface, Node ≥ 18.

Development

npm install        # dev-only deps (typescript, @types/node)
npm run build
npm test           # node:test unit suite (no network)
npm run smoke      # stdio handshake + tools/list against the built binary

License

Apache-2.0 — © AnvaiOps. An Anvai Labs project.