"A tool for retrieving error lists from codebases" matching MCP servers:

Enables creating and managing collections of items by adding entries, checking them off, and deleting them through MCP tools.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Enables LLM agents to search and analyze Elasticsearch logs for errors, detect recurring patterns, analyze error-rate trends, and retrieve full trace context through MCP tools.

Classifies agent errors and provides clear recovery actions (retry, escalate) with configurable categories and strategies, plus MCP tools for direct agent use.

Enables AI assistants to create, read, update, delete, and manage Slack List items, providing full task management within Slack through natural language.

Enables AI assistants to interact with Slack Lists through comprehensive tools for creating, retrieving, filtering, and managing list items. Supports bulk operations, data export, subtask creation, and all Slack List field types with robust error handling and production-ready implementation.

Explains known developer errors offline and deterministically (CORS, ESM/CommonJS, npm ERESOLVE, Next.js builds, Postgres connection and DATABASE_URL errors). One tool, explain_error; no LLM, no network.

An MCP server that enables Claude to learn from user corrections by recording them as persistent rules in CLAUDE.md files. It manages project-specific or global guidelines to ensure the assistant avoids repeating the same mistakes in future sessions.

Provides intelligent error detection and debugging capabilities across multiple programming languages with real-time monitoring of build, lint, runtime, console, and test errors. Offers AI-enhanced error analysis with automated resolution suggestions and context-aware debugging.

An open-source MCP server that collects errors from browser console and terminal, then uses OpenRouter's free AI models to generate summaries for AI agents.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

Provides tools for logging, confirming, and triaging issues with the semfora-engine, enabling AI agents to report bugs discovered during workflows.

Automates error tracking workflow by finding code owners in Bitbucket, retrieving related pull requests, and creating assigned JIRA tickets for code errors.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Turns application errors into reviewed pull requests by automating root-cause analysis, Jira ticket creation, local and CI test gates, and GitHub PRs, with a human as the final merge gate.

A Model Context Protocol server that provides a scratchpad tool for LLMs to organize thoughts, take notes, and plan approaches to complex problems.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.