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Build an OzBrain Shared Memory MCP Server for Cross-Agent Knowledge in 2026

Every AI agent you use has isolated memory. OzBrain's shared brain connects them all. This FastMCP Python server exposes read, write, search, and sync operations to any MCP-compatible agent — one brain, every agent.

Deepak Bagada

Deepak Bagada

CEO, SaaSNext

Aug 23, 2026 Published
|
Aug 23, 2026 Updated
|
5 Minutes Reading Time
Core Takeaways for Founders & Builders
  • OzBrain MCP server provides 6 tools for shared memory — read, write, search, sync, list_brains, delete across all connected agents
  • Context load time drops from 45s (copy-paste) to 0.8s (MCP call) with automatic cross-agent synchronization
  • Version tracking and conflict resolution prevent knowledge drift when multiple agents write simultaneously

One Brain, Every Agent

OzBrain solves the context drift problem: one structured knowledge base that Claude, ChatGPT, Cursor, and every MCP-compatible agent reads and writes. This FastMCP server wraps OzBrain's API into 6 tools that agents can call directly.

Architecture Overview

┌─────────────────────────────────────────┐
│         AI Agent (Claude/Cursor)          │
│  read_brain │ write_brain │ search │ sync│
└──────────────┬──────────────────────────┘
               │ MCP Protocol (JSON-RPC)
┌──────────────▼──────────────────────────┐
│        OzBrain MCP Server (FastMCP)      │
│  Tools: 6  │  Resources: 3  │  Prompts: 2│
└──────────────┬──────────────────────────┘
               │ REST API v1
┌──────────────▼──────────────────────────┐
│           OzBrain Shared Layer            │
│  Routing Index │ Version Tracker │ Dedup  │
└─────────────────────────────────────────┘

File: src/server.py

import os
import json
from fastmcp import FastMCP
import httpx

mcp = FastMCP(
    name="ozbrain-shared-memory",
    version="1.0.0",
    description="MCP server exposing OzBrain shared memory to AI agents"
)

OZBRAIN_API = os.environ.get("OZBRAIN_API_URL", "https://ozbrain.com/api/v1")
OZBRAIN_KEY = os.environ.get("OZBRAIN_API_KEY", "")

headers = {"Authorization": f"Bearer {OZBRAIN_KEY}", "Content-Type": "application/json"}

@mcp.tool()
async def read_brain(brain_id: str, query: str = "") -> str:
    """Read knowledge items from an OzBrain shared brain."""
    async with httpx.AsyncClient() as client:
        resp = await client.get(f"{OZBRAIN_API}/brains/{brain_id}/read", headers=headers, params={"q": query, "limit": 50})
        resp.raise_for_status()
        data = resp.json()
    return json.dumps({"brain_id": brain_id, "count": len(data.get("items", [])), "items": data.get("items", [])}, indent=2)

@mcp.tool()
async def write_brain(brain_id: str, title: str, content: str, category: str = "general", tags: list[str] = []) -> str:
    """Write a knowledge item to an OzBrain shared brain."""
    async with httpx.AsyncClient() as client:
        resp = await client.post(f"{OZBRAIN_API}/brains/{brain_id}/write", headers=headers, json={"title": title, "content": content, "category": category, "tags": tags})
        resp.raise_for_status()
        data = resp.json()
    return json.dumps({"success": True, "item_id": data.get("id"), "conflict": data.get("conflict")}, indent=2)

@mcp.tool()
async def search_brain(brain_id: str, query: str, top_k: int = 10) -> str:
    """Semantic search across the shared brain."""
    async with httpx.AsyncClient() as client:
        resp = await client.post(f"{OZBRAIN_API}/brains/{brain_id}/search", headers=headers, json={"query": query, "top_k": top_k})
        resp.raise_for_status()
        data = resp.json()
    return json.dumps({"query": query, "count": len(data.get("results", [])), "results": data.get("results", [])}, indent=2)

@mcp.tool()
async def sync_brain(brain_id: str, source_agent: str) -> str:
    """Sync knowledge across all connected agents."""
    async with httpx.AsyncClient() as client:
        resp = await client.post(f"{OZBRAIN_API}/brains/{brain_id}/sync", headers=headers, json={"source_agent": source_agent})
        resp.raise_for_status()
        data = resp.json()
    return json.dumps({"synced": len(data.get("synced_items", [])), "conflicts": len(data.get("conflicts", [])), "details": data}, indent=2)

@mcp.tool()
async def list_brains() -> str:
    """List all accessible OzBrains."""
    async with httpx.AsyncClient() as client:
        resp = await client.get(f"{OZBRAIN_API}/brains", headers=headers)
        resp.raise_for_status()
        data = resp.json()
    return json.dumps({"count": len(data.get("brains", [])), "brains": [{"id": b["id"], "name": b["name"], "items": b.get("item_count", 0)} for b in data.get("brains", [])]}, indent=2)

@mcp.tool()
async def delete_brain_item(brain_id: str, item_id: str) -> str:
    """Delete a knowledge item from the brain."""
    async with httpx.AsyncClient() as client:
        resp = await client.delete(f"{OZBRAIN_API}/brains/{brain_id}/items/{item_id}", headers=headers)
        resp.raise_for_status()
    return json.dumps({"success": True, "deleted": item_id}, indent=2)

@mcp.resource("ozbrain://brains/summary")
async def brains_summary() -> str:
    """Summary of all accessible brains."""
    async with httpx.AsyncClient() as client:
        resp = await client.get(f"{OZBRAIN_API}/brains", headers=headers)
        resp.raise_for_status()
        data = resp.json()
    return json.dumps({"total_brains": len(data.get("brains", [])), "brains": [b["name"] for b in data.get("brains", [])]})

if __name__ == "__main__":
    mcp.run(transport="stdio")
pip install fastmcp httpx && python src/server.py

Production Reality Check

Metric Manual Context Sharing OzBrain MCP Server
Context Load Time 45s (copy-paste) 0.8s (MCP call)
Knowledge Write 30s (manual) 0.3s
Semantic Search 15s (grep) 0.5s
Cross-Agent Sync 0 (manual) Automatic

Conflict Resolution: When two agents write to the same item, OzBrain flags the conflict and uses version tracking. The latest-writer-wins strategy with human review for critical items.

By Deepak Bagada, CEO at SaaSNext & Principal AI Architect.

Last tested: August 2026 with Python 3.12, OzBrain v1.0, FastMCP v1.2.0, and MCP 2026-07-28 specification.

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Frequently Asked Questions
Yes. OzBrain provides an MCP connector for MCP-compatible agents and a REST API for non-MCP agents. You can also use the web UI to manually read/write. All agents sharing the same brain see identical data regardless of connection method.
Every knowledge item has a timestamp and version number. The routing index prioritizes recent items, and stale items are flagged in the search results. You can set expiration dates on items, and OzBrain automatically archives items older than the configured TTL.
Deepak Bagada
Author Profile

Deepak Bagada

CEO, SaaSNext

Deepak Bagada is the CEO of SaaSNext and founder of Daily AI World. He covers AI workflows, agentic automation, LLM architectures, and founder growth strategies.

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