The Deepgram MCP connector routes your AI agent's tool calls to Deepgram's own MCP server through Scalekit. Each user signs in to Deepgram once, and Scalekit stores and refreshes their tokens, so your agent never handles credentials. It comes with 1 tool.
- Tools
- 1
- What they doRead · write · destructive
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- Users sign in with
- OAuth
- OAuth app
- Scalekit's or your own
Setup
Install the SDK
Terminal window npm install @scalekit-sdk/node dotenvTerminal window pip install scalekit-sdk-python python-dotenvSet your credentials
Add your Scalekit credentials to your
.envfile. Find values in app.scalekit.com > Developers > API Credentials..env SCALEKIT_ENVIRONMENT_URL=<your-environment-url>SCALEKIT_CLIENT_ID=<your-client-id>SCALEKIT_CLIENT_SECRET=<your-client-secret>Create the Deepgram MCP connection
In AgentKit > Connections, create a Deepgram MCP connection. The name you give it is the
connection_nameyour code passes. See Configure connections.Scalekit credentials are available for Deepgram MCP server, so you don't need to register an OAuth app.
Authorize a user and make your first call
quickstart.mts import { ScalekitClient } from '@scalekit-sdk/node'import 'dotenv/config'import { createInterface } from 'node:readline/promises'const scalekit = new ScalekitClient(process.env.SCALEKIT_ENVIRONMENT_URL,process.env.SCALEKIT_CLIENT_ID,process.env.SCALEKIT_CLIENT_SECRET,)const actions = scalekit.actionsconst connector = 'deepgrammcp'const identifier = 'user_123'// Generate an authorization link for the userconst { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })console.log('Authorize Deepgram MCP:', link)const rl = createInterface({ input: process.stdin, output: process.stdout })await rl.question('Press Enter after authorizing...')rl.close()// Make your first callconst result = await actions.executeTool({connector,identifier,toolName: 'deepgrammcp_search_deepgram_knowledge_sources',toolInput: { query: 'YOUR_QUERY' },})console.log(result)Terminal window npx tsx quickstart.mtsquickstart.py import osfrom scalekit import ScalekitClientfrom dotenv import load_dotenvload_dotenv()scalekit_client = ScalekitClient(env_url=os.getenv("SCALEKIT_ENVIRONMENT_URL"),client_id=os.getenv("SCALEKIT_CLIENT_ID"),client_secret=os.getenv("SCALEKIT_CLIENT_SECRET"),)actions = scalekit_client.actionsconnection_name = "deepgrammcp"identifier = "user_123"# Generate an authorization link for the userlink_response = actions.get_authorization_link(connection_name=connection_name,identifier=identifier,)print("Authorize Deepgram MCP:", link_response.link)input("Press Enter after authorizing...")# Make your first callresult = actions.execute_tool(tool_input={"query":"YOUR_QUERY"},tool_name="deepgrammcp_search_deepgram_knowledge_sources",connection_name=connection_name,identifier=identifier,)print(result)Terminal window python quickstart.pyEach user signs in once. See Authorize a user for the full flow and statuses.
Tools
Pass the exact name toexecute_tooldeepgrammcp_search_deepgram_knowledge_sourcesSearch Deepgram documentation and knowledge sources for the most relevant results for a given query.Read-onlySearch Deepgram Knowledge Sources
Search Deepgram documentation and knowledge sources for the most relevant results for a given query.
Inputs
querystringrequired- A single, well-formed natural-language query to search Deepgram knowledge sources. Must be a complete sentence.
No tools match.