"Pivotal Tracker" matching MCP servers:

Seed oil (PUFA) data for 500+ US restaurant chains: letter grades, the oil each chain fries in, cleanest menu items, and rankings. Zero-dependency Python stdio server backed by the free hosted Seed Oil Tracker endpoint, no key or account needed.

MCP server for tracking personal expenses via natural language, with tools to add, list, and summarize expenses, backed by Postgres.

Enables AI clients to track investment portfolios by retrieving positions, calculating profit and loss, and refreshing price data via Yahoo Finance. It allows users to monitor overall performance and query specific ticker details through natural language interactions.

This MCP enables access to Yandex Tracker issue management. Currently it supports all read operations to retrieve queues, issues and users from Yandex Tracker.

Enables tracking personal expenses by adding, listing, deleting, and summarizing expenses by day or month, stored locally in a JSON file.

A remote MCP server for expense tracking, providing tools to add, list, update, delete expenses, and generate summaries, budget status, and monthly trends.

An MCP server that lets Claude track, list, and summarize personal expenses through natural conversation, backed by SQLite and deployable locally or to FastMCP Cloud.

A TypeScript-based REST API that integrates project and task management with MCP (Model Context Protocol), allowing users to manage projects and tasks through natural language interactions.

Independent latency and uptime data for 46 hosted AI inference APIs, probed every 5 minutes from 4 regions with no gateway, plus a verified model deprecation calendar and Claude Code / Codex speed and accuracy drift. Four read-only tools, no API key; data CC BY 4.0.

Enables AI agents to manage Kanban boards, cards, sessions, and automations through a unified MCP interface with real-time updates, supporting delegation, agent sessions, and human-in-the-loop interactions.

Telegram Mini App MCP server exposing live product price tracking via tg.zovo.one

Manage your finances through natural language directly in your AI assistant. Add, edit, delete, and query expenses; set monthly budgets; and generate comprehensive spending reports seamlessly.

Enables AI assistants to manage personal finances through natural language, including adding, editing, listing, and deleting expenses, organizing them into categories, and setting monthly budgets with overspend warnings. It also provides spending summaries with month-over-month comparisons, budget status checks, and exportable Markdown or CSV reports, all backed by PostgreSQL storage with Google OAuth-authenticated per-user accounts.

Enables querying price history and undercut alerts for tracked competitors, allowing an assistant to check if a competitor has recently undercut your prices.

Provides real-time hurricane tracking, 5-day forecast cones, location-based alerts, and historical storm data from NOAA/NHC through MCP tools for AI assistants.

Enables ChatGPT, Claude, and other MCP clients to read, search, add, update, and delete entries in a personal specialty coffee collection, plus retrieve favorites and collection statistics. Connects over Streamable HTTP with OAuth-based owner approval and dynamically registered clients, so no API keys are needed.

Enables AI assistants to work with Yandex Tracker through its API, letting them search, create, edit, close, and bulk-manage issues, comments, checklists, time entries, attachments, queues, boards, dashboards, projects, and automation workflows. It also supports read-only mode for safe viewing integrations.

Local-first cost tracking and model routing for MCP agents with offline token counting, budget alerts, and spend reports.

Enables AI assistants to register, monitor, and query express delivery tracking numbers, with automatic background polling and status-change notifications returned through tool results.

Enables tracking food intake and nutrition using the USDA FoodData Central database. Supports logging meals, setting daily nutrition goals, viewing food diaries, and analyzing nutrition trends over time with local SQLite storage.