A Python package that combines Google's Gemma language model with MCP (Model Content Protocol) server integration, enabling powerful function calling
A Python package that combines Google's Gemma language model with MCP (Model Content Protocol) server integration, enabling powerful function calling capabilities across both local functions and remote MCP tools. Exposed over MCP by the gemma mcp mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
Everything the assistant can do here goes through one of these:
Testing — The package includes support for testing with in-memory MCP servers:GemmaMCPClient — The main client class that handles both Gemma model interactions and MCP tool integrationParameters — The Parameters tool exposed by this serverMethods — The Methods tool exposed by this serverFunctionDefinition — The FunctionDefinition tool exposed by this serverYou will need one environment variable: GEMINI_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
google-genai: Google Generative AI Python SDK - FastMCP MCP utilitiesInstallation goes through your MCP client rather than a global install: point it at gemma-mcp on PyPI and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Among the knowledge and memory options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Gemma MCP's toolset — Testing, GemmaMCPClient, Parameters and 2 more — is a fair guide to whether it matches your workflow. It is maintained by monatis; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Gemma MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Testing | The package includes support for testing with in-memory MCP servers: |
| GemmaMCPClient | The main client class that handles both Gemma model interactions and MCP tool integration. |
| Parameters | The Parameters tool exposed by this server. |
| Methods | The Methods tool exposed by this server. |
| FunctionDefinition | The FunctionDefinition tool exposed by this server. |
2. servers with STDIO transport:
```python
mcp_config = {
"mcpServers": {
"server_name": {
"command": "python",
"args": ["./server.py"]
}
}
}Configuration as documented by the project. Restart the client after saving.
google-genai: Google Generative AI Python SDK - FastMCP MCP utilities| Variable | Description | Required |
|---|---|---|
| GEMINI_API_KEY | Credential the server authenticates with. | Yes |
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.