"General search for 'es'" matching MCP servers:

Enables full-text search of macOS iMessages including link preview metadata. Works as an MCP server for Claude Desktop to search your messages locally.

Downloads your entire Search Console dataset into a local SQLite database, then gives your LLM a pre-built SQL query library for every standard SEO analysis type, with context available for your LLM to perform any SQL query to answer your questions and analyse for you.

Connect AI assistants to Manticore Search. Execute SQL queries, list tables, get schemas, and fetch documentation. Perfect for building RAG applications and search-powered AI agents.

Enables AI clients to search and read over 2,400 New York City public datasets through the Socrata SODA API, with ready-made tools for restaurant health inspections and 311 service requests plus general dataset discovery and querying.

Enables AI systems to perform full-text and semantic search operations over structured/unstructured data in Azure Cognitive Search, with capabilities for document indexing and management through natural language.

A general-purpose MCP server that lets AI work with multiple databases within clear boundaries.

Provides access to Naver Search APIs, allowing AI agents to search across multiple categories (blogs, news, books, images, shopping items, etc.) with structured responses optimized for LLM consumption.

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.

An MCP server that enables interaction with Elasticsearch and OpenSearch clusters for searching documents and managing indices. It provides tools for cluster health monitoring, index configuration, and general API requests.

Provides comprehensive tools for managing Elasticsearch clusters, including security management, search operations, and index administration. It enables users to monitor cluster health, handle InfoSec tasks, and execute complex queries using Elasticsearch Query DSL and ES|QL.

A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.

Enables LLMs to query a synthetic general ledger and trial balance through read-only tools for account lookups, GL drill-down, variance analysis, and naive forecasting, with every answer cited to specific transactions or periods.

MCP server that aggregates job listings from Remotive and Arbeitnow, with local SQLite caching, application tracking, and saved searches.

Enables AI agents to look up Chinese laws and statutory articles fully offline from a local SQLite database, resolving a law name plus article number to verbatim text, searching articles by keyword, and retrieving a law's chapter structure and version history. It also verifies citations in bulk, checking whether each quoted provision exists word-for-word and is currently in force.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

This read-only MCP Server allows you to connect to Google Search data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Enables agents to list indices, read mappings, run query DSL and ES|QL searches, and inspect shards on an Elasticsearch cluster through its HTTP API.

Provides LLMs with full PostgreSQL database access, including tools for query execution, schema management, and data export. It also features a dedicated insights system for storing business memos and supports both local stdio and remote HTTP transport.

Enables AI assistants to interact with Odoo ERP systems through natural language, allowing users to search, create, update, and manage business records like customers, products, and invoices across any Odoo instance.

Enables AI assistants to search, query, and manage Azure AI Search indexes using full-text, semantic, and vector search, alongside index and document operations.

A general-purpose MCP server for Firebase that enables natural language interaction with Firestore, Auth, Storage, and Cloud Functions logs through schema-driven validation and context-efficient tools.

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.

A Model Context Protocol server that searches transcript segments in a Turso database using vector similarity, allowing users to find relevant content by asking questions without generating new embeddings.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables users to query the CVE-Search API to browse vendors and products, retrieve CVEs by ID, list vulnerabilities for vendor/product combinations, fetch recent CVEs with CAPEC/CWE/CPE expansions, and inspect database information.

MCP server for searching and retrieving Korean accounting standards (K-IFRS, general corporate accounting standards) and Q&A summaries from the KASB database. Provides four tools: keyword search of standards and Q&As, real-time full text of standards, and cached Q&A details.

Enables Claude to search developer jobs by frontend stack such as React, Vue.js, Angular, TypeScript, and Next.js, and retrieve matching job details with application links from a local SQLite database.

An MCP server that indexes local Python projects into a SQLite database to enable efficient symbol searching and dependency tracking. It allows users to find function or class definitions, trace module imports, and read file contents through natural language interfaces.

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