Generate MCP Server

speakeasy auth login
# Or for CI/AI agents:
export SPEAKEASY_API_KEY="<your-api-key>"

speakeasy lint openapi --non-interactive -s ./openapi.yaml

# After all config files are in place:
speakeasy run

# mcp-scopes-overlay.yaml
openapi: 3.1.0
overlay: 1.0.0
info:
  title: Add MCP scopes
  version: 0.0.0
actions:
  # Enable read operations
  - target: $.paths.*["get","head"]
    update:
      x-speakeasy-mcp:
        scopes: [read]
        disabled: false

  # Enable write operations
  - target: $.paths.*["post","put","delete","patch"]
    update:
      x-speakeasy-mcp:
        scopes: [write]
        disabled: false

  # Disable specific sensitive endpoints (customize as needed)
  # - target: $.paths["/admin/danger-zone"]["delete"]
  #   update:
  #     x-speakeasy-mcp:
  #       disabled: true

# .speakeasy/workflow.yaml
workflowVersion: 1.0.0
speakeasyVersion: latest
sources:
  My-API:
    inputs:
      - location: ./openapi.yaml
    overlays:
      - location: mcp-scopes-overlay.yaml
    output: openapi.yaml
targets:
  mcp-server:
    target: mcp-typescript
    source: My-API

# .speakeasy/gen.yaml
configVersion: 2.0.0
generation:
  sdkClassName: MyApiMcp
  maintainOpenAPIOrder: true
  devContainers:
    enabled: true
    schemaPath: ./openapi.yaml
typescript:
  version: 1.0.0
  packageName: my-api-mcp
  envVarPrefix: MYAPI

speakeasy run

speakeasy run --output console 2>&1 | tail -50

# Start with stdio transport (default, for local AI assistants)
npx my-api-mcp mcp start --bearer-auth "YOUR_TOKEN"

# Start with SSE transport (for networked deployment)
npx my-api-mcp mcp start --transport sse --port 3000 --bearer-auth "YOUR_TOKEN"

# Filter by scope (only expose read operations)
npx my-api-mcp mcp start --scope read --bearer-auth "YOUR_TOKEN"

# Mount specific tools only
npx my-api-mcp mcp start --tool users-get-users --tool users-create-user --bearer-auth "YOUR_TOKEN"

{
  "mcpServers": {
    "my-api": {
      "command": "npx",
      "args": [
        "-y", "--package", "my-api-mcp",
        "--",
        "mcp", "start",
        "--bearer-auth", "<API_TOKEN>"
      ]
    }
  }
}

{
  "mcpServers": {
    "my-api": {
      "command": "npx",
      "args": [
        "-y", "--package", "my-api-mcp",
        "--",
        "mcp", "start",
        "--bearer-auth", "<API_TOKEN>"
      ]
    }
  }
}

# Build and run
docker-compose up -d

# Configure MCP client to use SSE endpoint
# "url": "http://localhost:32000/sse"

# 1. Validate the spec
speakeasy lint openapi --non-interactive -s ./petstore.yaml

# 2. Create scopes overlay
cat > mcp-scopes-overlay.yaml << 'EOF'
openapi: 3.1.0
overlay: 1.0.0
info:
  title: Add MCP scopes
  version: 0.0.0
actions:
  - target: $.paths.*["get","head"]
    update:
      x-speakeasy-mcp:
        scopes: [read]
        disabled: false
  - target: $.paths.*["post","put","delete","patch"]
    update:
      x-speakeasy-mcp:
        scopes: [write]
        disabled: false
EOF

# 3. Create workflow (assumes .speakeasy/ dir exists)
mkdir -p .speakeasy
cat > .speakeasy/workflow.yaml << 'EOF'
workflowVersion: 1.0.0
speakeasyVersion: latest
sources:
  petstore:
    inputs:
      - location: ./petstore.yaml
    overlays:
      - location: mcp-scopes-overlay.yaml
    output: openapi.yaml
targets:
  mcp-server:
    target: mcp-typescript
    source: petstore
EOF

# 4. Create gen.yaml
cat > .speakeasy/gen.yaml << 'EOF'
configVersion: 2.0.0
generation:
  sdkClassName: PetStoreMcp
  maintainOpenAPIOrder: true
typescript:
  version: 1.0.0
  packageName: petstore-mcp
  envVarPrefix: PETSTORE
EOF

# 5. Generate
speakeasy run

# 6. Test locally
npx petstore-mcp mcp start --bearer-auth "test-token"

Workflow completed successfully.
Generated TypeScript MCP server in ./