Project README

Source: README.md at f0c3d3702a6cf77529a8ecd307103558484dffee. This is a repository snapshot, not a claim about the latest published release.

intpot

intpot: Python tools served as CLI, API, or MCP

Part of ModePot. Project website Created by Tugrul Guner

One typed definition. Three interfaces.

Define typed tools once for CLI, HTTP, or MCP. Convert apps between Typer, FastAPI, and FastMCP.

Quick start · Playground · Deep docs · README quick start · Convert an app · Conversion scope · Architecture · Community · Contributing

Intpot uses the same normalized ToolInfo schema in two workflows: registered Python tools can be served or ejected as CLI, API, or MCP interfaces, while existing Typer, FastAPI, or FastMCP apps can be inspected and converted into standalone code

Why intpot?

A useful Python function often needs three interfaces: a command for people, an HTTP endpoint for applications, and an MCP tool for AI agents. Maintaining three copies means three signatures, three sets of descriptions, and three places for behavior to drift.

intpot gives you two ways out:

Starting point	What intpot does
Plain Python functions	Register them once with `@app.tool()`, then serve or eject CLI, API, and MCP interfaces
An existing Typer, FastAPI, or FastMCP app	Inspect it, normalize its tools, and generate either of the other two frameworks

The output is ordinary Python. Ejected and converted apps do not depend on intpot.

Quick start

Install every runtime for the complete experience:

pip install "intpot[all]"

Write once, serve everywhere

Save this as app.py:

from intpot import App

app = App("my-app")

@app.tool()
def add(a: int, b: int) -> int:
    """Add two numbers together."""
    return a + b

@app.tool()
def greet(name: str, greeting: str = "Hello") -> str:
    """Greet someone by name."""
    return f"{greeting}, {name}!"

Then serve in any mode:

intpot serve app.py --cli          # Run as Typer CLI
intpot serve app.py --api          # Run as FastAPI on port 8000
intpot serve app.py --mcp          # Run as MCP server for AI agents

In CLI mode, everything after the flags belongs to your app:

$ intpot serve app.py --cli add 2 3
5
$ intpot serve app.py --cli greet World --greeting Hi
Hi, World!

With API mode running, call the same names as POST routes with JSON request bodies:

$ curl -s -X POST http://127.0.0.1:8000/add \
    -H "Content-Type: application/json" \
    -d '{"a": 2, "b": 3}'
5

MCP mode exposes add and greet as FastMCP tools with schemas derived from their type annotations and defaults.

Or eject to standalone framework code:

intpot eject app.py --to api       # Export as standalone FastAPI app
intpot eject app.py --to cli       # Export as standalone Typer CLI
intpot eject app.py --to mcp       # Export as standalone FastMCP server

Scaffold a new project

intpot init my-server --type mcp
intpot init my-app --type cli
intpot init my-api --type api

Install only the frameworks you need if you do not want the full extra:

pip install intpot          # Core commands and Typer output
pip install "intpot[mcp]"   # Add FastMCP support
pip install "intpot[api]"   # Add FastAPI support

Convert an existing app

intpot detects Typer, FastAPI, and FastMCP apps from a Python file and supports every conversion between them:

# MCP server -> Typer CLI
intpot to cli server.py

# CLI app -> FastMCP server
intpot to mcp app.py

# CLI app -> FastAPI app
intpot to api app.py

# Write output to a file
intpot to cli server.py --output cli_app.py

# Convert all apps in a directory
intpot to cli ./myproject/
intpot to mcp ./myproject/ --output ./converted/

Directory output mirrors the source tree, so myproject/alpha/tools.py becomes converted/alpha/tools_mcp.py. Sources sharing a filename in different packages stay separate files.

Use intpot inspect app.py first when you want to see the normalized tool definitions before generating code. Converted output is readable Python that you can review, test, and change.

Give your coding agent intpot context

Install project-local instructions for Claude Code, Cursor, Windsurf, GitHub Copilot, Cline, or OpenAI Codex:

# Auto-detect agents in your project
intpot add skills

# Target a specific agent
intpot add skills --agent claude
intpot add skills --agent cursor
intpot add skills --agent windsurf
intpot add skills --agent copilot
intpot add skills --agent cline
intpot add skills --agent codex

# Specify a project directory
intpot add skills --path ./myproject/

What intpot handles

One definition, three live interfaces: serve an intpot.App through Typer, FastAPI, or FastMCP.
Six conversion directions: move existing apps between all three frameworks.
Standalone output: eject or convert to normal framework code with no intpot runtime dependency.
Behavior-aware transforms: preserve recoverable function bodies and the direct imports they use, and translate framework conventions such as typer.echo() into return values.
Interface fidelity: carry types, defaults, and async functions through supported conversions, and apply FastAPI parameter sources when generating an API.
Inspectable semantic core: use intpot.load().schema for an immutable ApplicationSchema, inspect target projections before generation, or use detached ToolInfo compatibility objects through .tools.
Project tooling: scan directories, scaffold projects, and install agent guidance for six coding agents.

Python API

Universal App (write once, serve everywhere)

from intpot import App

app = App("my-app")

@app.tool()
def greet(name: str, greeting: str = "Hello") -> str:
    """Greet someone."""
    return f"{greeting}, {name}!"

# Serve as any framework
app.serve(mode="cli")                         # Run as Typer CLI
app.serve(mode="api", port=8000)              # Run as FastAPI on 127.0.0.1
app.serve(mode="mcp")                         # Run as MCP server

# Eject to standalone code
cli_code = app.eject("cli")                   # Returns Typer code string
api_code = app.eject("api")                   # Returns FastAPI code string

# Inspect the canonical application schema
print(app.schema.to_dict())
for tool in app.schema.tools:
    print(tool.name, tool.parameters)

Conversion API (convert existing framework code)

import intpot

# From a file
app = intpot.load("mcp_server.py")
api_schema = app.project("api")               # Immutable target semantics
cli_code = app.to_cli()
api_code = app.to_api()

# From a live instance
from fastmcp import FastMCP

mcp = FastMCP("my-server")

@mcp.tool()
def greet(name: str) -> str:
    return f"Hello, {name}!"

app = intpot.load(mcp)
print(app.to_cli())

# Write directly to a file
app.write("output/cli_app.py", "cli")
app.write("output/api_app.py", "api")

App (universal runtime):

.tool(name=None, description=None) — decorator to register functions as tools; both arguments override the defaults taken from the function name and docstring. Functions with *args or **kwargs are rejected because those parameters have no consistent CLI, HTTP API, and MCP representation.
.serve(mode, host, port) — serve as CLI, API, or MCP
.eject(target) — generate standalone framework code
.schema — immutable ApplicationSchema snapshot shared with conversion
.tools — detached ToolInfo compatibility objects

IntpotApp (conversion wrapper, returned by intpot.load()):

.to_cli(), .to_mcp(), .to_api() — return generated code as strings
.schema — immutable source ApplicationSchema, compiled once
.project(target) — immutable target projection used by generation
.write(path, target) — generate and write to a file in one step
.tools — detached ToolInfo compatibility objects; mutating them does not alter the schema
.source_type — detected framework type

What conversion preserves

intpot is designed to produce code you can own, rather than hide conversion behind a runtime adapter. ApplicationSchema is the application-level semantic boundary; immutable ToolSchema and ParameterSchema records carry the parts that the three frameworks share:

tool names, descriptions, types, defaults, and async behavior;
recoverable function bodies and the direct imports they reference;
framework metadata that has a target equivalent, including supported Query, Header, Path, and Body parameter sources when generating FastAPI;
scalar returns translated into a shape the target framework can serve correctly.

Frameworks do not have one-to-one equivalents for every feature. FastAPI dependencies (Depends, Security, nested dependencies, and route/router/app-level dependencies) are preserved by inspection, but API-to-CLI/MCP conversion refuses them with UnsupportedFastAPIDependencyError rather than emitting code with missing values. Full dependency injection mapping remains tracked in #20. Review generated code when a source uses nested Typer command groups, repeatable CLI options, Annotated[..., Body(...)], Pydantic model parameters, routes with multiple HTTP methods, streaming, background tasks, or framework-specific error handling.

intpot carries direct import statements referenced by a tool body. It does not yet copy same-module helpers, constants, classes, models, or closure values that the body references, and it does not follow dependencies across imported modules. Factory-created apps are not detected by the current AST pre-check. Loading a source file directly also does not add its directory to sys.path, so a sibling import such as from helpers import normalize may require installing the package or setting PYTHONPATH. External services and configuration are not provisioned for you. If intpot cannot recover a body, it emits a # TODO: implement stub instead of inventing behavior.

[!IMPORTANT] Detection imports the source module, so only inspect or convert code you trust. A source that cannot be parsed or imported is reported cleanly; during a directory conversion, intpot reports the bad file and continues with the rest. intpot is alpha software: compile the generated file, import it with its dependencies, and exercise a real CLI command, API request, or MCP tool before shipping it.

Architecture

Both halves of intpot meet at one canonical ApplicationSchema. It owns immutable ToolSchema and ParameterSchema records. Existing ToolInfo and ParameterInfo objects remain detached compatibility views at the edges.

   @app.tool()                        source .py file
   (intpot.App)                    (Typer / FastMCP / FastAPI)
        |                                    |
        |                              1. DETECT
        |                              2. INSPECT
        |                                    |
        +-----------> ApplicationSchema <----+
                           ToolSchema[]
                              |
              +---------------+---------------+
              |                               |
        build a live                    3. GENERATE
      framework instance            (render a template)
              |                               |
       serve --cli/--api/--mcp        .py output on disk
                                    (to cli/mcp/api, eject)

Conversion follows four stages: detect the framework, inspect its tools, compile one immutable ApplicationSchema, then project target-specific semantics before rendering. The runtime side compiles @app.tool() registrations into the same schema. serve keeps the registered callables for live execution; eject renders detached views of the stable schema. Access .schema.to_dict() when a human, build tool, or agent needs to inspect exactly what Intpot compiled.

to_dict() is directly JSON-serializable. Every non-JSON-native default uses an unambiguous {"$intpot": {"type": ...}} envelope, preserving distinctions such as list versus tuple and bytes versus an ordinary dictionary. Enum and opaque defaults, as well as timezone-aware/folded temporal values, are rejected with TypeError because standalone generated code cannot preserve their semantics reliably.

Conversion examples

The repository includes checked-in source and generated output for every direction:

Source	Typer target	FastAPI target	FastMCP target
Typer	—	`cli_to_api.py`	`cli_to_mcp.py`
FastAPI	`api_to_cli.py`	—	`api_to_mcp.py`
FastMCP	`mcp_to_cli.py`	`mcp_to_api.py`	—

examples/ also contains advanced inputs with direct imports, async tools, request bodies, Depends(), and path parameters. The FastAPI dependency example remains inspectable, but API-to-CLI/MCP conversion intentionally refuses it until issue #20 is implemented. The FastAPI input also includes routes with multiple HTTP methods. See semantic_schema.py for a runnable canonical-schema inspection example.

CLI Reference

intpot --version (or -V) prints the installed version; intpot <command> --help works for any command below.

`intpot serve`

Serve an intpot App as CLI, API, or MCP server.

intpot serve <source> --cli|--api|--mcp [--host <host>] [--port <port>] [--] [args...]

Argument/Option	Description
`source`	Path to a Python file containing an `intpot.App`
`--cli`	Serve as a Typer CLI
`--api`	Serve as a FastAPI app
`--mcp`	Serve as a FastMCP server
`--host`	API server host (default: `127.0.0.1` — pass `0.0.0.0` to expose it on the network)
`--port`	API server port (default: `8000`)
`args...`	Passed straight to your app in `--cli` mode: `intpot serve app.py --cli add 2 3`

Anything intpot doesn’t recognise is forwarded, so your own options work as-is. Use -- when your app defines a flag intpot also defines:

intpot serve app.py --cli -- greet World --port 5

`intpot inspect`

Show the tools intpot extracts from a source, without generating anything. Useful for checking what a conversion will see before you run it.

intpot inspect <source> [--json] [--verbose]

Argument/Option	Description
`source`	Path to a source Python file or directory
`--json`	Emit the canonical tool schema as JSON instead of a table
`--verbose`, `-v`	Print detection details to stderr

$ intpot inspect mcp_server.py

Source: mcp_server.py (mcp)
┏━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━┓
┃ Name  ┃ Description            ┃ Parameters            ┃ Return Type ┃ Async ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━┩
│ greet │ Greet someone by name. │ name: str, greeting:  │ str         │ No    │
│       │                        │ str='Hello'           │             │       │
└───────┴────────────────────────┴───────────────────────┴─────────────┴───────┘

`intpot eject`

Export an intpot App as standalone framework code.

intpot eject <source> --to <cli|mcp|api> [--output <path>]

Argument/Option	Description
`source`	Path to a Python file containing an `intpot.App`
`--to`, `-t`	Target framework: `cli`, `mcp`, `api` (required)
`--output`, `-o`	Output file path (prints to stdout if omitted). Missing parent directories are created

`intpot init`

Scaffold a new project from a template.

intpot init <name> --type <mcp|cli|api>

Argument/Option	Description
`name`	Project name (creates a directory)
`--type`, `-t`	Project type: `mcp`, `cli`, or `api` (required)

`intpot to cli` / `to mcp` / `to api`

Convert a source file — or every app in a directory — to the target framework. For a directory, the output mirrors the source tree: each generated file keeps its source’s position, with only the filename changing.

intpot to cli <source> [--output <path>] [--dry-run] [--verbose]
intpot to mcp <source> [--output <path>] [--dry-run] [--verbose]
intpot to api <source> [--output <path>] [--dry-run] [--verbose]

All three take the same arguments:

Argument/Option	Description
`source`	Path to a source Python file or directory
`--output`, `-o`	Output file/directory path (prints to stdout if omitted). Missing directories are created
`--dry-run`	Print what would be generated, without writing any files
`--verbose`, `-v`	Print detection details to stderr

to cli accepts MCP or API sources, to mcp accepts CLI or API, to api accepts CLI or MCP. A source that already matches the target is skipped.

--dry-run shows generated output without writing generated files, but it is not a sandbox: detection still imports the source and executes arbitrary module-level code. Only point intpot at source you trust:

$ intpot to cli mcp_server.py --dry-run
# --- Would generate: mcp_server_cli.py ---
"""CLI app generated by intpot."""
...

`intpot add skills`

Install intpot skills/rules for AI coding agents. Auto-detects which agents are configured in the project, or specify one explicitly.

intpot add skills [--agent <name>] [--path <dir>]

Option	Description
`--agent`, `-a`	Target agent: `claude`, `cursor`, `windsurf`, `copilot`, `cline`, `codex`
`--path`, `-p`	Project root directory (defaults to current directory)

Supported agents and output locations:

Agent	Detected by	Files created
Claude Code	`.claude/`	`.claude/skills/intpot-cli/SKILL.md`, `.claude/skills/intpot-python/SKILL.md`
Cursor	`.cursor/`	`.cursor/rules/intpot-cli.mdc`, `.cursor/rules/intpot-python.mdc`
Windsurf	`.windsurf/`	`.windsurf/rules/intpot-cli.md`, `.windsurf/rules/intpot-python.md`
GitHub Copilot	`.github/copilot-instructions.md`	`.github/copilot-instructions.md` (managed block)
Cline	`.clinerules/`	`.clinerules/intpot-cli.md`, `.clinerules/intpot-python.md`
OpenAI Codex	never auto-detected	`AGENTS.md` (managed block)

Codex has to be asked for by name — intpot add skills --agent codex. It reads AGENTS.md, but so does nearly every other tool now, so the presence of that file says nothing about whether you use Codex. Since installing appends to it, guessing wrong would edit your own documentation. The same reasoning is why Copilot keys off .github/copilot-instructions.md rather than .github/, which only means the project is on GitHub.

Running with no --agent and no detected marker exits without writing anything. Copilot and Codex installations use bounded intpot-managed blocks, so rerunning the command updates or repairs intpot guidance while preserving surrounding project content. For Codex, intpot warns when the resulting AGENTS.md exceeds Codex’s default 32 KiB instruction limit.

Community

The ModePot Discord is the shared community for intpot, summonpot, dexpot, and the rest of the project family. Join to discuss use cases, ask implementation questions, and help shape declaration-first Python frameworks.

Use GitHub issues for reproducible bugs and scoped feature proposals. Use Discord for open-ended design discussion, early ideas, and help applying the frameworks to real projects.

Contributing

intpot has a small core with clear extension points: inspectors turn frameworks into ToolInfo, generators turn ToolInfo into source, and runtime builders expose live interfaces. Contributions can improve conversion fidelity, add real-world examples, strengthen generated-code tests, or make the developer experience clearer.

Start with a good first issue.
Browse work where help is wanted.
Read CONTRIBUTING.md for the pull request process and docs/reviewing.md for the contracts changes must preserve.

Open an issue before substantial public-contract work; focused fixes, tests, documentation, and maintenance may be direct pull requests. User-facing work uses an issue-backed or Towncrier-generated orphan changelog fragment—never a pull-request-number fragment.

Development setup

Requires uv.

git clone https://github.com/tugrulguner/intpot.git
cd intpot
uv sync --all-extras
uv run pre-commit install

Run the full check suite:

make check   # lint + typecheck + test

Individual targets:

make lint              # ruff check + format check
make typecheck         # pyright
make test              # pytest
make format            # auto-format code
make changelog-draft   # preview the next release section
make changelog         # assemble changelog.d/ into CHANGELOG.md (release only)

Changelog entries are written as one fragment file per PR in changelog.d/ rather than by editing CHANGELOG.md, and CI asks every PR for one. See changelog.d/README.md — it’s short.

Roadmap

See ROADMAP.md for the current polish backlog and the planned full AST transform pipeline.

Support intpot

If intpot removes a duplicate interface from your project, consider starring the repository. Stars help other Python developers find the project, while issues and pull requests make it better.

License

MIT