This file contains examples of how to use the VFB3-MCP server tools.
{
"method": "tools/call",
"params": {
"name": "get_term_info",
"arguments": {
"id": "VFB_jrcv0i43"
}
}
}{
"method": "tools/call",
"params": {
"name": "run_query",
"arguments": {
"id": "VFB_00101567",
"query_type": "PaintedDomains"
}
}
}{
"method": "tools/call",
"params": {
"name": "search_terms",
"arguments": {
"query": "medulla"
}
}
}{
"method": "tools/call",
"params": {
"name": "search_terms",
"arguments": {
"query": "medulla",
"filter_types": ["neuron", "adult"],
"exclude_types": ["deprecated"]
}
}
}{
"method": "tools/call",
"params": {
"name": "search_terms",
"arguments": {
"query": "medulla",
"minimize_results": true,
"rows": 20
}
}
}{
"method": "tools/call",
"params": {
"name": "search_terms",
"arguments": {
"query": "antennal lobe",
"auto_fetch_term_info": true
}
}
}{
"method": "tools/call",
"params": {
"name": "resolve_entity",
"arguments": {
"name": "P{VT054895-GAL4.DBD}"
}
}
}{
"method": "tools/call",
"params": {
"name": "find_stocks",
"arguments": {
"feature_id": "FBst123456",
"collection_filter": "Bloomington"
}
}
}{
"method": "tools/call",
"params": {
"name": "resolve_combination",
"arguments": {
"name": "SS04495"
}
}
}{
"method": "tools/call",
"params": {
"name": "find_combo_publications",
"arguments": {
"fbco_id": "FBco_0001234"
}
}
}{
"method": "tools/call",
"params": {
"name": "list_connectome_datasets",
"arguments": {}
}
}{
"method": "tools/call",
"params": {
"name": "query_connectivity",
"arguments": {
"upstream_type": "FBbt_00000001",
"downstream_type": "FBbt_00000002",
"weight": 5,
"group_by_class": true,
"exclude_dbs": ["hemibrain"]
}
}
}Add to your MCP server configuration:
{
"mcpServers": {
"vfb3-mcp": {
"type": "http",
"url": "https://vfb3-mcp.virtualflybrain.org",
"tools": ["*"]
}
}
}Add to your claude.json:
{
"mcpServers": {
"vfb3-mcp": {
"type": "http",
"url": "https://vfb3-mcp.virtualflybrain.org",
"tools": ["*"]
}
}
}Configure the MCP server URL in your Copilot settings pointing to https://vfb3-mcp.virtualflybrain.org.
To use the Virtual Fly Brain (VFB) Model Context Protocol (MCP) server with AI on Google Search, connect through the Gemini CLI or a custom Python/Node.js client.
The Gemini web interface does not directly support custom MCP integration. Developer tools are needed to connect the two.
Option 1: Using Gemini CLI
The Gemini CLI allows direct registration of remote MCP servers.
Install the CLI: Ensure Node.js is installed, then run:
npm install -g @google/gemini-cliAdd the VFB Server: Use the add command with the VFB URL.
gemini mcp add vfb https://vfb3-mcp.virtualflybrain.orgVerify & Use: Run the CLI by typing gemini. Check the connection with /mcp. AI on Google Search will then call VFB's neuroanatomy and connectivity tools when questions about Drosophila are asked.
Option 2: Using Python
For application development, use the mcp and google-genai libraries to connect.
Setup: pip install google-genai mcp
Implementation: Use a streamable HTTP transport in JSON response mode (e.g. enableJsonResponse: true) to connect to the VFB URL, list its tools, and pass their schemas to the Gemini model as Function Declarations.
# Build and run
docker-compose up --build
# Or manually
docker build -t vfb3-mcp .
docker run -it vfb3-mcp