"A server for automatically scanning and loading database table structures into AI agent context" matching MCP servers:

Converts Excel table definitions to structured JSON and exposes them to LLMs via MCP tools like list_tables and get_table_schema, enabling accurate SQL generation and data modeling assistance.

A lightweight MCP server for semantic search over markdown knowledge bases, enabling AI coding agents to index, search, and answer questions from local markdown documents.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

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

Two-way Burp Suite MCP bridge enabling AI agents to capture traffic, analyze endpoints, queue scans, and send findings back to Burp.

MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

A read-only MCP server that enables AI agents to explore database schemas and execute safe queries on PostgreSQL and MySQL.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Tracks working context and code structure in a portable local SQLite database, enabling seamless context and task continuity across different AI coding tools.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Provides deterministic decision and constraint evaluation for AI agents. Supports ruleset validation, fact evaluation, and constraint checking via MCP tools.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.

A local-first bridge for moving useful context between coding agents, indexing sessions and creating handoff packets for seamless agent switching.

A local MCP server that gives AI coding agents persistent memory and context across sessions.

An MCP Server that enables users to interact with Google's On-Demand Scanning API (v1beta1) through natural language, likely providing capabilities for vulnerability scanning and security analysis of containers and artifacts.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.