A Model Context Protocol server that exposes Microsoft Edge browsing history across multiple profiles, allowing listing profiles and fetching history for a given day.
Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.
Enables MCP clients to securely query databases, list tables, inspect table schemas, and test connections across Oracle, SQL Server, MySQL, PostgreSQL, and SQLite using read-only SQL tools.
Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.
A read-only MCP server for exploring and analyzing a Secoda data catalog, enabling AI chat, semantic search, glossary browsing, and data lineage tracing.
Converts SQL queries between different database dialects using the sqlglot library to ensure cross-system compatibility. It allows users to list supported dialects and transpile SQL code from one syntax to another through the Model Context Protocol.
A Model Context Protocol server that exposes Firebase Firestore and Authentication to AI agents, supporting multi-project configurations and read operations.
Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.
MCP server that allows Claude AI to interact directly with MySQL databases, enabling query execution and table information retrieval through natural language.
A production-style MCP server exposing six business tools (web search, database, CRM, email, calendar, analytics) to AI clients via a secure, authenticated interface, with mock mode and a reference agent client.
Enables AI models to interact with MySQL databases through MCP protocol, supporting queries, table schema inspection, and data manipulation operations.
Enables AI clients to securely interact with Oracle databases using natural-language prompts, translating requests into structured queries and returning results for AI-powered data access.
Enables AI clients to interact with PostgreSQL databases through natural language, translating requests into structured queries and returning results via a secure self-hosted server.
Enables a unified AI assistant that combines document retrieval (RAG), database queries via MCP tools, and web search, allowing users to ask complex questions and receive answers from multiple enterprise sources.