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Entwicklung · SKILL.md

core-sdk

core-sdk

Build local mcp-agent apps with MCPApp, Agent, AgentSpec, AugmentedLLM, RequestParams, settings, secrets, decorators, and factory basics.

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Skill-Dokumentation

GitHub

name: core-sdk description: "Build local mcp-agent apps with MCPApp, Agent, AgentSpec, AugmentedLLM, RequestParams, settings, secrets, decorators, and factory basics." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

core-sdk

Use this sub-skill when the task is to create, configure, or debug a local mcp-agent application using the core Python SDK. It covers MCPApp, Agent, AgentSpec, AugmentedLLM, RequestParams, programmatic Settings, YAML config/secrets, local function tools, human-input hooks, and the basic agent factory helpers.

Start Here

  1. Read references/api-reference.md for verified constructor signatures, lifecycle patterns, LLM attachment, provider/model selection, and request parameters.
  2. Read references/configuration.md when the task involves mcp_agent.config.yaml, mcp_agent.secrets.yaml, Settings(...), provider keys, or schema validation.
  3. Read references/decorators-and-factory.md for @app.tool, @app.async_tool, workflow decorator basics, AgentSpec, create_agent, create_llm, and agent-spec loading.
  4. Read references/troubleshooting.md when imports, provider extras, secrets, YAML merging, server names, async lifecycle, decorators, or RequestParams fail.
  5. Run scripts/check_core_sdk.py --help to see the credential-free smoke checks; run it before blaming provider credentials or network access.

Core Workflow

  • Create one MCPApp per process, preferably with an explicit Settings object or explicit config path for deterministic runs.
  • Enter async with app.run() as running_app: before using app context, configured server registry, logging, token counters, human-input hooks, or workflow decorators that depend on runtime context.
  • Define Agent(name=..., instruction=..., server_names=[...], functions=[...], context=running_app.context) for local agents; attach a provider implementation with await agent.attach_llm(...) only after provider package and credentials are available.
  • Use RequestParams(...) per generation to set model, model preferences, temperature, token limits, tool filtering, history, iteration count, strict mode, and reasoning effort.
  • Keep provider keys in secrets or environment variables; keep reusable server/model defaults in config or programmatic Settings.

Route Elsewhere

  • Route workflow pattern selection, routers/orchestrators/parallel/deep workflow design, and durable workflow strategy to sibling workflow-patterns.
  • Route MCP server exposure, server auth internals, FastMCP deployment, and app-as-server details to sibling mcp-server-integration.
  • Route CLI commands, cloud deployment, and hosted operations to sibling cli-cloud-operations.
  • Route Temporal worker operations and production durability to sibling durable-execution.
  • Route tracing/exporter/provider-wrapper internals to sibling observability-integrations.

Bundled Check

Use the smoke checker for local SDK validation without credentials or network:

python scripts/check_core_sdk.py
python scripts/check_core_sdk.py --provider openai

The default check imports core APIs, constructs programmatic settings, validates local function-tool annotations, registers decorators, creates an AgentSpec, and builds RequestParams. Provider checks only import the provider wrapper and report whether a key-shaped setting is present; they do not call external services.

Gespeicherte Skills