"New product development resources and information" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables AI assistants to discover, retrieve, and compare official international development indicators from sources such as the World Bank, FAOSTAT, WHO, UNICEF, and IMF, while preserving source identifiers, units, and citations.

Enables retrieving New York Consolidated Laws by citation, including full statutory text, effective dates, and searchable law corpora.

MCP server for ERP product operations that enables AI agents to precheck product packages, upload files, and create products automatically without manual token copying.

Enables triaging product feedback over a local dataset, including search, theme clustering, severity tagging, and drafting PRD-ready problem statements.

Enables CRUD operations and search on an Excel-backed product catalog, allowing users to list, search, add, update, and delete products.

A Model Context Protocol server that enables seamless integration between Claude AI and development tools like VSCode, Augment, Vercel, Airtable, and Square.

A production-ready MCP server that provides comprehensive dbt project quality assessment for any GitHub repository, enabling AI agents to analyze dbt models, check metadata coverage, and map data lineage.

A full-feature MCP server that serves as a product-development copilot, providing RAG search, SQL queries, and inline chart visualizations from seeded product data, with per-user identity and its own OAuth login.

Enables agents to explore a project's captured events and properties, then run trend, funnel and retention analyses and create or list saved insights. Tools are model-oriented, returning trimmed, budgeted results and actionable errors, with the project resolved from the API key or bearer token rather than passed as an argument.

Turns product ideas into implementation-ready planning packages including PRD, requirements, user flow, wireframes, data schema, API contracts, and SDK boundaries, with an MCP handoff for coding agents.

Enables retrieval of New Jersey Statutes (N.J.S.A.) section text by citation, including parsed amendment history, plus keyword-based full-text topic search returning ranked sections with citation and heading. Keyless access to the state legislature's statute data.

Enables Amazon search and product data extraction, returning titles, prices, ASINs, and listings as clean JSON through MCP.

Enables extraction of product names, prices, and currency from e-commerce pages through a single API call, with built-in anti-bot handling and protected-page support.

Provides secure PDF template analysis and layout extraction for AI assistants, enabling generation of styled HTML with automatic image generation.

An MCP server that exposes SF Supplies product search API to LLM tools. Supports free-text search, autocomplete suggestions, and retrieving filterable attributes.

Open-source home design and floor plan editor for AI agents: draw walls and rooms, place furniture, doors and windows, build kitchens and wardrobes, check lighting, ergonomics, electrical and plumbing against building codes, and render the plan, 3D views or photorealistic images. Runs in the desktop app, the browser or the hosted server, and every change can be undone.

Facilitates spec-driven development workflows by providing structured prompts for generating requirements in EARS format, design documents, and implementation code following a systematic approach.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Enables AI agents to inspect any public domain’s web technology stack, email deliverability and DNS health (MX, SPF, DKIM, DMARC, MTA-STS, TLS-RPT, BIMI), and HTTPS security posture with typed JSON scores and remediation-ready findings, plus history, bulk checks, monitoring alerts, and reverse technology lookups.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Enables comprehensive Google Meet and Calendar management through Google Calendar API v3 and Google Meet API v2, supporting calendar event creation with Meet links, space management, transcription, recording, attendance tracking, and meeting moderation controls.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.