"Troubleshooting and debugging errors" matching MCP servers:

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

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.

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.

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.

ContextLattice is an HTTP-first, MCP-compatible memory/context/task orchestrator that persists writes and returns fused recall from specialized stores with local-first defaults. Primary URL: https://contextlattice.io/ Install: https://contextlattice.io/installation.html Troubleshooting: https://contextlattice.io/troubleshooting.html

Agent failure memory network. Search 235+ verified debugging lessons from real engineering sessions. Includes guided prompts for failure triage and release auditing.

Zero-dependency token optimizer, test-failure triage gate, and System 1.5 semantic guardrail for AI coding agents. Intercepts compiler errors, missing dependencies, and doom loops in < 500µs.

MCP server for AI agent deployment health — gateway status, CPU/memory/swap, recent errors from journalctl/dmesg, skill registry integrity, upgrade outcomes, cron + disk usage. Each component gets HEALTHY/DEGRADED/CRITICAL classification with overall rollup.

Enables Codex and Claude Code to delegate implementation, research, debugging, and long-log work to DeepSeek Harness, then observe, continue, or cancel those sessions without leaving the primary workflow.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A 66-tool reasoning pipeline that intercepts prompts to classify intent, check past mistakes, and generate execution plans, enabling any LLM to think harder and avoid repeating errors.

Bridges coding agents such as Claude Code and Hermes to Brave Leo AI over the Model Context Protocol, letting the agent delegate execution to reduce token usage. Enables skills like refactoring, debugging, planning, and web search through Brave AI.

Enables MCP clients to control Chrome/Edge browsers via CDP, including page navigation, element interaction, snapshots, network debugging, script execution, and performance tracing.

An MCP server that gives AI agents faithful control of real, logged-in Chrome profiles via a secure local bridge and extension, with exact multi-profile routing and no debug profiles or remote debugging ports.

A local MCP server that forwards tools from an upstream experiment platform and adds AI Agent tools for experiment analysis and skill debugging.