"GitHub repository for litopys-dev/litopys project" matching MCP servers:

Provides aggregated municipal development costs for US jurisdictions, including impact fees and utility connection charges, enabling AI agents to assess building feasibility quickly.

MCP server that silently monitors state changes in structured data sources (e.g., government open data) and provides a pull-based channel for AI agents to retrieve real mutations since their last cursor.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

An MCP server that provides real-time weather alerts for US states using the National Weather Service (NWS) API. It also includes utility features for message echoing and generating customizable greeting prompts.

Torify gives AI agents the Japanese locale primitives that standard libraries lack — imperial era date conversion (wareki), qualified invoice number validation with NTA registry lookup, corporate number lookup (法人番号), postal code resolution, name romanization (Hepburn), and kanji-to-kana conversion via Yahoo! JLP. 31 endpoints total. No authentication required for MCP. Pay-per-call $0.02/call via

A Python FastMCP server that re-exposes Kindora's public funder and grant tools for ChatGPT, enabling grant discovery from IRS 990 filings and Grants.gov.

Enables users to search and query information about military service alternative companies in South Korea through the Military Manpower Administration (MMA) API. Supports filtering by service type, industry, company size, location, and recruitment status.

MCP server for structured Australian macroeconomic and financial data from the Australian Bureau of Statistics (ABS), the Reserve Bank of Australia (RBA), and the Australian Prudential Regulation Authority (APRA).

Cost of living, CPI, PPP, and regional price data for 190+ countries. Semantic endpoints with natural language parameters. MCP server for AI agents.

Facilitates retrieval of National Park Services data using the NPS API, allowing users to list national parks by state and access detailed information about specific parks.

Enables AI assistants to search Japanese government subsidies and grants, including archived closed calls and recurring application periods based on historical data.

Exposes Denmark's Statistical Bureau API as programmable resources, making it easy to integrate with language models and modern AI applications to enable natural language queries for statistical data.

OpenLawMCP is an open-source legal AI research tool built to make AI-assisted legal research more reliable. A major problem with using AI for legal research is that it can give confident answers without showing whether the answer is grounded in real legal sources. For legal work, that creates a credibility problem. Users need answers that can be checked against actual legal material.

Enables natural language access to Denmark's Statistics API (Danmarks Statistik), allowing users to query and analyze Danish statistical data without coding knowledge through AI-powered interactions.

Provides real SEC EDGAR filings as MCP tools, allowing agents to fetch clean, cited, token-lean filing data from a single URL with no installation.

US + EU salary benchmarking, pay transparency compliance, and semantic endpoints. 1,400+ US occupations, 28 EU countries. MCP server for AI agents.

EU economic statistics — GDP, inflation, unemployment, trade, population

Enables querying of Korean building ledger information including property details, floor plans, and pricing via natural language.

LA County ADU buildability checks, zoning rules, permit trends, and cost estimates — free, no auth.

Enables querying and retrieving daily feeds of newly incorporated Canadian federal companies, with filters for incorporation date, province, keywords, and incremental updates, returning structured company data including addresses and directors.