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A lightweight, file-based function execution engine.

Project description

Brimley

Application server for function-based AI tooling, focused on faster iteration loops.

Status: Brimley is not yet ready for production use. It is aimed at improving the MCP development workflow and is still under active development.

Brimley is an application server that discovers, validates, and executes function-based AI tooling. It owns its own process and event loop, providing three operating modes: an interactive REPL for development, a headless MCP server for production, and a one-shot invoke mode for scripting and CI. The core focus is reducing the change/test loop during MCP tool development: change code → reload → re-test.

Design goals

  • Faster iteration loop: author tools in .py, .sql, .md, and .yaml files and execute them immediately, without a full redeploy cycle.
  • Safer change workflow: discovery is AST-first for Python (no import-time execution during scan), with diagnostics instead of immediate process termination.
  • Live runtime ergonomics: use a thin REPL client attached to a daemon-owned runtime, with optional watch-mode reload.
  • MCP integration path: expose selected functions as MCP tools via FastMCP when needed.
  • Declarative HTTP and CLI integration (0.7+): wrap external APIs and shell commands as first-class Brimley functions using YAML — no boilerplate code required.
  • Managed dependency injection (0.8+): @provider, Depends(), @on_startup/@on_shutdown hooks, and BrimleyContainer with singleton and request scopes — shared resources with proper lifecycle semantics.
  • Application server ownership (0.9+): Brimley owns its process and event loop. No embedding inside other Python applications — integrate externally via MCP.
  • Operations clarity: built-in reload diagnostics, runtime error surfacing, and explicit daemon lifecycle controls.

Architectural approach

Brimley is an application server — it always owns its process and event loop. It separates tool authoring/execution semantics from MCP transport hosting:

  • Brimley handles discovery, schemas, argument resolution, execution, reload policy, and diagnostics.
  • FastMCP (optional) handles MCP server transport.

Keeping function logic separate from transport makes it reusable across all three operating modes:

Mode Command Purpose
REPL brimley repl Interactive development with hot-reload, admin commands, and optional embedded MCP.
MCP Server brimley mcp-serve Headless production mode — serves tools over SSE/stdio.
Invoke brimley invoke <name> One-shot function execution for scripting, CI, and debugging. No background services are started.

Note: Embedding Brimley as a library inside another Python application (e.g., importing into FastAPI) is not supported. External applications integrate with Brimley via MCP as a sidecar process.

Quick Start

1) Install

poetry install

Optional MCP support:

poetry install -E fastmcp

2) Add brimley.yaml

brimley:
  app_name: "Brimley App"

config:
  support_email: "support@example.com"

state:
  request_count: 0

databases:
  default:
    connector: sqlite
    url: "sqlite:///./data.db"

auto_reload:
  enabled: true

mcp:
  host: 127.0.0.1
  port: 8000

3) Add a Python function (calc.py)

from brimley import function

@function(mcpType="tool")
def calculate_tax(amount: float, rate: float = 8.25) -> float:
    return round(amount * (rate / 100.0), 2)

4) Run REPL

PYTHONPATH=src poetry run brimley repl --root .

5) Invoke once from CLI

PYTHONPATH=src poetry run brimley invoke calculate_tax --root . --input "{amount: 100, rate: 8.25}"

Core CLI Commands

  • brimley repl --root . [--mcp|--no-mcp] [--watch|--no-watch]
  • brimley repl --root . --shutdown-daemon
  • brimley mcp-serve --root . [--watch|--no-watch] [--host HOST] [--port PORT]
  • brimley invoke <function_name> --root . --input "{...}"
  • brimley build --root . [--output PATH]
  • brimley validate --root . [--format text|json] [--fail-on warning|error] [--output PATH]
  • brimley schema-convert --in schema.yaml --out fieldspec.yaml [--allow-lossy]

MCP Integration

Mark a function as an MCP tool:

  • Python: @function(mcpType="tool")
  • SQL/Template/API/CLI frontmatter:
mcp:
  type: tool

API and CLI functions defined in .yaml files are first-class MCP tools. See API Functions and CLI Functions.

Then serve tools with:

PYTHONPATH=src poetry run brimley mcp-serve --root .

Runtime Model (0.9 architecture baseline)

Brimley is an application server that owns its process and event loop. It does not support being embedded as a library inside another Python application.

  • REPL mode: Thin client attached to a daemon-owned runtime. Daemon owns state, watcher lifecycle, and optional embedded MCP hosting.
  • MCP server mode: Headless process serving tools over SSE/stdio via FastMCP.
  • Invoke mode: One-shot function execution — no daemon, no background services, no task scheduler.
  • /detach leaves daemon running; /quit (or --shutdown-daemon) terminates daemon session.
  • Reload is partitioned and diagnostics-driven; schema-shape tool changes require MCP client reconnect.

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