
JSON DB MCP Server
Enables users to manage data in a simple JSON file database through MCP tools and REST API. Supports creating, reading, updating, and deleting items organized in collections with auto-generated UUIDs.
README
JSON DB MCP Server (FastAPI + FastMCP)
A minimal Model Context Protocol (MCP) server that also exposes a small REST API.
Data is stored in a single JSON file (db.json
) as collections of items with auto-generated UUIDs.
- MCP Tools:
db.add_item
,db.get_item
,db.list_items
,db.update_item
,db.delete_item
- REST Endpoints:
POST/GET/PUT/DELETE /db/{collection}[/{id}]
- Transports: HTTP (recommended) and SSE (optional)
- Stack: Python, FastAPI, Uvicorn, FastMCP
Features
- Simple JSON-file database with atomic writes
- Thread-safe in a single-process server using a lock
- Shared core logic for both MCP tools and REST
- Works with VS Code Copilot (Chat) and Gemini CLI as an MCP server
Requirements
- Python 3.10+
uv
(recommended) orpip
- Git (optional, for version control)
Project Layout
.
├─ main.py
├─ db.json # created on first write
└─ README.md
Installation
Using uv
(recommended)
uv venv
uv pip install fastapi uvicorn fastmcp
Using pip
python -m venv .venv
source .venv/bin/activate
pip install fastapi uvicorn fastmcp
Running
Development (auto-reload)
uv run main.py
# or
uv run python main.py
# Server: http://localhost:8000
Default MCP transport: HTTP at
/mcp/
(recommended).
If you prefer SSE, see MCP over SSE (optional) below.
REST API
All endpoints operate on a collection (created on first write) with items of shape:
{
"id": "uuid-string",
"...": "fields you provide"
}
Create
curl -X POST http://localhost:8000/db/users \
-H "Content-Type: application/json" \
-d '{"name":"Omar","role":"admin"}'
List
curl http://localhost:8000/db/users
Get by ID
curl http://localhost:8000/db/users/<ITEM_ID>
Update
curl -X PUT http://localhost:8000/db/users/<ITEM_ID> \
-H "Content-Type: application/json" \
-d '{"role":"owner"}'
Delete
curl -X DELETE http://localhost:8000/db/users/<ITEM_ID>
MCP Server (HTTP transport, recommended)
This server mounts FastMCP’s HTTP transport at /mcp/
.
VS Code — GitHub Copilot (Chat)
- Open Copilot Chat → Tools (or Add MCP).
- Transport:
HTTP
- URL:
http://localhost:8000/mcp/
(include the trailing slash) - Enable the server. You should see tools:
db.add_item
,db.get_item
,db.list_items
,db.update_item
,db.delete_item
Using tools in chat:
Select a tool from the list or ask:
Use
db.add_item
withcollection="users"
andpayload={"name":"Omar"}
.
Gemini CLI
Add the server via CLI (writes settings for you):
# Project-scoped (./.gemini/settings.json)
gemini mcp add --transport http jsondb http://localhost:8000/mcp/
# Or user-scoped (~/.gemini/settings.json)
gemini mcp add --scope user --transport http jsondb http://localhost:8000/mcp/
List tools:
gemini mcp list
Call a tool:
gemini mcp call jsondb db.add_item \
--args collection=users \
--args payload='{"name":"Omar"}'
MCP over SSE (optional)
If you prefer SSE, change the mount in main.py
:
# replace the HTTP mount:
# mcp_http_app = mcp.http_app(path="/")
# app.mount("/mcp", mcp_http_app)
mcp_sse_app = mcp.sse_app()
app.mount("/mcp", mcp_sse_app) # SSE lives under /mcp/sse/
- SSE endpoint:
http://localhost:8000/mcp/sse/
(note trailing slash) - Copilot: Transport =
SSE
, URL =http://localhost:8000/mcp/sse/
- Gemini CLI:
gemini mcp add --scope user --transport sse jsondb http://localhost:8000/mcp/sse/
Many HTTP clients require a trailing slash for SSE endpoints; use
/mcp/sse/
.
Health Check (optional)
Add this to main.py
(after app = FastAPI(...)
) if you want a friendly root:
@app.get("/")
def health():
return {"ok": True, "rest": "/db/{collection}", "mcp": "/mcp/"}
Persistence & Backups
- Data file:
db.json
(created on first write). - Writes are atomic: a
db.json.tmp
is written then replaced. - For safety, consider periodic snapshots (e.g.,
cp db.json db.json.bak
in a cron job).
Authentication (optional)
For local development MCP/REST are open.
If you need auth, simplest is an API key header via FastAPI middleware and headers in your MCP client configuration. Example:
from fastapi import Request
from fastapi.responses import JSONResponse
import os
API_KEY = os.getenv("API_KEY", "")
@app.middleware("http")
async def api_key_guard(request: Request, call_next):
if API_KEY and request.headers.get("x-api-key") != API_KEY:
return JSONResponse(status_code=401, content={"detail": "Unauthorized"})
return await call_next(request)
- Copilot/Gemini: configure an
x-api-key
header in the MCP server settings.
Troubleshooting
-
404 on
/
Expected. Use REST under/db/...
and MCP at/mcp/
(HTTP) or/mcp/sse/
(SSE). -
307 redirect from
/mcp
→/mcp/
Some SSE clients don’t follow redirects. Use the trailing slash or disable redirect slashes:app.router.redirect_slashes = False
-
SSE returns 404
Make sure you’re hitting/mcp/sse/
(not/mcp/
). -
Concurrency
Run as a single process for file-backed DB. Multi-process/worker deployments need a real DB or OS-level file locks. -
Git push errors (VS Code AskPass socket)
Unset helper vars or use GitHub CLI / SSH keys:unset GIT_ASKPASS SSH_ASKPASS VSCODE_GIT_ASKPASS_NODE VSCODE_GIT_ASKPASS_MAIN
License
Copyright© - Omar SOLIMAN
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.