ivcap-lambda: Python SDK for Lambda-Style IVCAP Services

Package renamed: ivcap-ai-tool has been renamed to ivcap-lambda to reflect that the library is useful for any lambda-style IVCAP service, not just AI agent tools. A compatibility shim is published under the old name — existing apps will continue to work but will see a DeprecationWarning prompting migration.

ivcap-lambda is a Python library that turns a plain Python function into a set of IVCAP-compatible HTTP endpoints and/or a spec-compliant MCP (Model Context Protocol) server, from the same tool code. It sits on top of ivcap-service and FastAPI, and handles:

• Registering tool functions as HTTP endpoints (with async "try-later" semantics)
• Job execution in threads, result caching, and graceful shutdown
• Event/progress reporting back to the IVCAP platform
• Automatic tool-description endpoints (for AI agents) and an optional MCP endpoint (built on the official mcp Python SDK)

📖 Full documentation: https://ivcap-works.github.io/ivcap-ai-tool-sdk-python/

🚀 New to the library? Depending on your goal:

• Building a service for the IVCAP platform (MCP optional) → see AGENTS.md, Track A or the Quick Start guide
• Building an MCP server first, with IVCAP deployment as a bonus → see AGENTS.md, Track B or the MCP guide's MCP-first section
• A ready-to-clone starter project → ivcap-python-ai-tool-template

Installation

pip install ivcap-lambda

# To also expose tools as an MCP server:
pip install ivcap-lambda[mcp]

Minimal Example

from pydantic import BaseModel, Field
from ivcap_service import Service, getLogger, with_schema
from ivcap_lambda import start_lambda_server, ivcap_lambda, ToolOptions, logging_init

logging_init()
logger = getLogger("my-service")

service = Service(
    name="My IVCAP Service",
    description="A minimal example service.",
    contact={"name": "Alice", "email": "alice@example.com"},
    license={"name": "MIT", "url": "https://opensource.org/licenses/MIT"},
)


@with_schema("urn:example:schema:echo.request.1")
class EchoRequest(BaseModel):
    message: str = Field(..., description="The message to echo back.")


@with_schema("urn:example:schema:echo.1")
class EchoResult(BaseModel):
    echo: str = Field(..., description="The echoed message.")


@ivcap_lambda("/", opts=ToolOptions(tags=["Echo"]))
def echo(req: EchoRequest) -> EchoResult:
    """Echo a message

    Returns the message passed in the request unchanged.
    """
    return EchoResult(echo=req.message)


if __name__ == "__main__":
    start_lambda_server(service)

Run and test it:

python my_service.py --port 8090
curl -X POST http://localhost:8090/ -H "content-type: application/json" -d '{"message": "Hello, IVCAP!"}'

# Or, with the mcp extra installed, run the exact same tool as an MCP server instead:
python my_service.py --with-mcp-stdio

For everything else — defining tools, ToolOptions, JobContext, progress reporting, artifacts, MCP, project layout, deployment, Docker — see the full documentation and AGENTS.md. This README intentionally stays limited to installation/quick-start plus notes for anyone working on ivcap-lambda itself (below), to avoid duplicating content that's already maintained in the docs site.

Migration from ivcap-ai-tool

The old ivcap-ai-tool package is a compatibility shim that re-exports everything from ivcap-lambda. It will emit a DeprecationWarning at import time. No code changes beyond the import are required.

Contributing / Developing ivcap-lambda Itself

The sections below are for anyone extending, fixing, or releasing this library — not for consumers of the package. See also CONTRIBUTING.md, DESIGN.md (internal architecture), and CONDUCT.md.

Repository Layout

ivcap-ai-tool/
├── ivcap_lambda/    # the library itself
├── compat/          # ivcap-ai-tool deprecation shim (old package name)
├── docs/            # MkDocs documentation site (docs/docs) + build output (docs/site)
├── examples/        # runnable example services (test-tool, test-mcp)
├── tests/           # unit tests
├── AGENTS.md        # user-facing reference for AI coding agents
├── DESIGN.md        # internal architecture & design rationale
└── pyproject.toml

Setup, Tests & Checks

poetry install
make test    # pytest --cov=ivcap_lambda
make check   # test + ruff check + mypy

Running the Example Services

cd examples/test-tool && poetry install && make run   # REST example
cd examples/test-mcp  && poetry install && make run   # MCP example (HTTP)
cd examples/test-mcp  && make run-mcp-stdio            # MCP example (stdio)

Building & Serving the Documentation Site

make docs-serve   # live-reload at a random local port
make docs-build   # build static site into docs/site

Releasing

Versioning/publishing is driven by semantic_release config in pyproject.toml on main. make build / make publish wrap poetry build/poetry publish.

License

Licensed under the BSD-style license in LICENSE. See AUTHORS.md for contributors.