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

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

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

Enables AI agents to securely reach enterprise tools and other agents through a governed gateway with pinned tool definitions, delegated authorization, content inspection, human approval, and signed audit trails.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

Enables AI agents to claim, heartbeat, submit, split, park, and resume atomic work-queue tasks, with fencing tokens and receipts, while storing and versioning records and content-addressed files through MCP.

Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Enables enterprise MCP clients and partner agents to execute tenant-isolated underwriting, claims, and compliance workflows with durable step checkpointing, evidence-grounded tool calls, and deterministic PDF citation receipts. It supports A2A task dispatch and MCP JSON-RPC operations while blocking cross-tenant access and ungrounded deliverables.

Enables Grok Bots to install, verify, build, seal, unseal, list, and update hash-pinned skill packs from static URLs, expanding skill capacity beyond template limits without executing pack content.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

An authless Cloudflare Workers server that provides tools to scrape, analyze, and answer questions about websites using Cloudflare's Browser Rendering and AI capabilities.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

A Model Context Protocol server that provides real-time Caltrain schedule information, allowing AI assistants to look up train departures between any stations and access station information using GTFS data.

MCP server to interact with Grupr agents, enabling polling new messages, posting replies, and managing event webhooks.

Enables orchestrating external AI agents to execute development tasks with asynchronous management, automated acceptance verification, failure rework loops, and optional visual baseline validation.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Acts as a personal AI development environment manager, enabling workspace bootstrapping, headless skill and bundle installation, global caching, and health diagnostics.

A server implementing Model Context Protocol that enables LLMs to interact with the ZenML platform, providing access to pipeline data, stack information, and the ability to trigger new pipeline runs.

Enables AI agents to access a collection of specialized agent instructions on demand, covering categories like tech, business, growth, and product.

A FastMCP server that helps users discover, browse, and install agent skills from curated GitHub collections, with support for adding new skill sources.

A durable multi-agent orchestrator for software development with explicit run graphs, checkpoint/resume capabilities, and project memory exposed through MCP resources and tools. It enables coordinated agent workflows for coding, review, repair, CI, and approval with SQLite-backed memory retrieval and pluggable research backends.

Multi-Agent Development Agentic Network that enables AI-driven software development through specialized agents, interactive wizards, and structured debate, with MCP integration for IDE tools like workflow execution, impact analysis, and ecosystem search.

Enables users to leverage a team of specialized AI agent personas like Business Analysts and Product Managers through a unified interface across multiple LLM providers. It streamlines agile development workflows by providing tools for model discovery, unified prompt delivery, and role-specific decision making.

A server that implements the Model Completion Protocol (MCP) to allow LLMs to interact with Databricks resources including clusters, jobs, notebooks, and SQL execution through natural language.

Orchestrates multiple AI agents (Product Manager, Software Architect, Engineer, QA, Reviewer) to collaboratively plan, design, implement, review, and improve software development projects via MCP tools.