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developing-genkit-tooling

developing-genkit-tooling

github.com/genkit-aiDevelopment6.6k54 installsUpdated today
Repository

About developing-genkit-tooling

developing-genkit-tooling is a practical guide for developers building Genkit tooling, covering CLI commands and MCP tools. It defines naming conventions, runtime interaction patterns, and error handling.

Key features

  1. 01CLI subcommand naming conventions
  2. 02MCP tool naming conventions
  3. 03Static and runtime tool architecture
  4. 04Genkit project runtime interaction patterns
  5. 05Structured error responses

Use cases

  1. 01Add CLI commands to Genkit
  2. 02Register MCP tools for a project runtime
  3. 03Implement static MCP tools for documentation

MCP support

The guide describes building Genkit MCP tools, including static documentation tools and tools that require a project runtime.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/genkit-ai/genkit --skill developing-genkit-tooling

After installing, type/developing-genkit-toolingin Claude Code to confirm it loaded.

Details

From the project README

Developing Genkit Tooling

Naming Conventions

Consistency in naming helps users and agents navigate the tooling.

CLI Commands

Use kebab-case with colon separators for subcommands.

  • Format: noun:verb or category:action
  • Examples: flow:run, eval:run, init
  • Arguments: Use camelCase in code (flowName) but standard format in help text (<flowName>).
MCP Tools

Use snake_case for tool names to align with MCP standards.

  • Format: verb_noun
  • Examples: list_flows, run_flow, list_genkit_docs, read_genkit_docs

CLI Command Architecture

Commands are implemented in cli/src/commands/ using commander.

Runtime Interaction

Most commands require interacting with the user's project runtime. Use the runWithManager utility to handle the lifecycle of the runtime process.

import { runWithManager } from '../utils/manager-utils';

// ... command definition ...
.action(async (arg, options) => {
  await runWithManager(await findProjectRoot(), async (manager) => {
    // Interact with manager here
    const result = await manager.runAction({ key: arg });
  });
});
Output Formatting
  • Logging: Use logger from @genkit-ai/tools-common/utils.
  • Machine Readable: Provide options for JSON output or file writing when the command produces data.
  • Streaming: If the operation supports streaming (like flow:run), provide a --stream flag and pipe output to stdout.

MCP Tool Architecture

MCP tools in cli/src/mcp/ follow two distinct patterns: Static and Runtime.

Static Tools (e.g., Docs)

These tools do not require a running Genkit project context.

  • Registration: defineDocsTool(server: McpServer)
  • Dependencies: Only the server instance.
  • Use Case: Documentation, usage guides, global configuration.
Runtime Tools (e.g., Flows, Runtime Control)

These tools interact with a specific Genkit project's runtime.

  • Registration: defineRuntimeTools(server: McpServer, options: McpToolOptions)
  • Dependencies: Requires options containing manager (process manager) and projectRoot.
  • Schema: MUST use getCommonSchema(options.explicitProjectRoot, ...) to ensure the tool can accept a projectRoot argument when required (e.g., in multi-project environments).
// Runtime tool definition pattern
server.registerTool(
  'my_runtime_tool',
  {
    inputSchema: getCommonSchema(options.explicitProjectRoot, {
      myArg: z.string(),
    }),
  },
  async (opts) => {
    // Resolve project root before action
    const rootOrError = resolveProjectRoot(
      options.explicitProjectRoot,
      opts,
      options.projectRoot
    );
    if (typeof rootOrError !== 'string') return rootOrError;

    // access manager via options.manager
  }
);
Error Handling

MCP tools should generally catch errors and return them as content blocks with isError: true rather than throwing exceptions, which ensures the client receives a structured error response.

try {
  // operation
} catch (err) {
  const message = err instanceof Error ? err.message : String(err);
  return {
    isError: true,
    content: [{ type: 'text', text: `Error: ${message}` }],
  };
}

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