FI-MCP
Provides AI assistants with access to 30+ validated financial independence calculation functions, eliminating hallucinations by ensuring accurate calculations for retirement planning, CoastFI, investment returns, and other FI metrics.
README
FI-MCP
Model Context Protocol (MCP) server for the Financial Independence community.
Overview
FI-MCP automatically generates MCP tools from the FI function library using introspection. This allows AI assistants to access the financial independence calculation functions we use as native tools. This gets rid of hallucinations by ensuring that the AI uses the right calculations for the job, rather than guessing or taking a random calculation from the web. It also boosts confidence for the user because it allows us to know where the calculation is coming from. Math can be checked in the FI library and the associated blog article or forum link (where applicable).
Features
- Auto-discovery: Automatically finds all functions in the FI library
- Type-safe: Converts Python type annotations to MCP tool schemas
- Parameter validation: Validates and converts arguments before function calls
- Comprehensive coverage: All 30+ FI functions available as MCP tools
Installation
For development:
# Clone the repository
cd /path/to/FI-MCP
# Install package with dev dependencies in editable mode
pip install -e .[dev]
For production use:
pip install .
Configuration for AI Editors
Add these setttings to your Windsurf MCP config file, Claude ~/.claude/config.json,
or other analogous file:
{
"mcpServers": {
"fi-mcp": {
"command": "python",
"args": ["-m", "fi_mcp.server"],
"env": {
"PYTHONUNBUFFERED": "1"
}
}
}
}
After adding the configuration, restart your editor. The AI assistant will now have access to all FI calculation tools.
Usage
Once configured, you can ask your AI assistant questions like:
- "Calculate my CoastFI number with $50k invested, 4% return, retiring at 65, currently 30"
- "How much does it cost to buy a day of freedom with $40k annual spending?"
- "How do I calculate cap rate?" - Get full documentation including what it calculates, parameters, and credits
- "I don't remember how to calculate turnover costs" - Get full documentation including what it calculates, parameters, and credits
- "What inputs does future_value take?" - See all parameters with descriptions
- "Show me all available FI calculations" - Browse all available functions
The AI will automatically use the appropriate FI tool to perform a FI related calculation. It can access complete markdown-formatted docstrings for any function, including detailed explanations, parameter descriptions, return values, and attribution credits.
Available Tools
See the FI library for the full list of available tools.
Architecture
FI-MCP uses introspection patterns to:
- Discover all functions in the FI module
- Extract parameter types and descriptions from function signatures and markdown docstrings
- Generate MCP tool schemas automatically
- Expose function documentation via MCP Resources
- Handle type conversion and validation
- Execute functions with converted arguments
MCP Features
- Tools: Each FI function is exposed as an MCP tool with full type information and parameter descriptions
- Resources: Function documentation is available via
fi://help/{function_name}URIs, returning markdown-formatted docstrings
Development
Setup
Install the package in editable mode with development dependencies:
pip install -e .[dev]
Running Tests
Run all tests:
pytest -v
Run specific test file:
pytest tests/test_docstring_validation.py -v
pytest tests/test_basic.py -v
Test Coverage
tests/test_docstring_validation.py- Validates that all FI functions have proper markdown docstringstests/test_basic.py- Integration tests for function discovery, schema generation, and execution
License
MIT License - Same as FI library
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。