"General information or troubleshooting related to errors" matching MCP servers:

MCP server exposing four task-shaped tools (resolve, pay, verify, disclose) for General Liquidity, enabling agents to normalize counterparties, submit intents, verify disclosures, and produce signed disclosures.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Enables MCP clients to query proxy sub-accounts, traffic, pricing, and inventory, and to place orders, renew, and modify configurations after user confirmation.

Enables agents to discover available still-image animation models, obtain credit quotes without charge, submit one explicitly approved generation job, and poll the resulting short clip.

Enables searching government awards through the Sell to State API by proxying JSON-RPC to the live HTTP MCP endpoint, requiring an API key.

Lightweight project management for teams and AI agents.

MCP server for searching French and European law, providing natural language access to jurisprudence, consolidated legal texts, and related legal information via tools like search_decisions and search_legal_texts.

Provides AI-enabled access to Amazon Business API documentation, sample code, and troubleshooting resources. Enables developers to search and retrieve API documentation, generate integration code, and get guided solutions for common errors during the API integration process.

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.

Provides tools for discovering, building, deploying, and troubleshooting AWS Deep Learning Containers (DLC) images. Supports multiple frameworks and instance recommendations.

Reduces log files to remove noise and duplicate information, cutting tokens by 70-90% for AI agents, preserving only errors, warnings, and unique events.