AI Agent for Solr MCP
Seamlessly connect FlowHunt with your Apache Solr collections using the Solr MCP integration. Enable advanced, secure document search for your Large Language Model (LLM) workflows. Instantly empower AI agents to retrieve, filter, and analyze documents stored in Solr using the Model Context Protocol (MCP) standard. Boost accuracy and speed for AI-powered search, research, and data-driven applications.
Advanced Solr Search with LLM Integration
Leverage the power of Solr MCP to provide your AI agents with robust document search, filtering, and retrieval capabilities. Effortlessly connect Apache Solr collections to FlowHunt and allow direct, secure, and scalable access for your LLMs. Optimize knowledge discovery, automate research, and power intelligent applications with real-time Solr data.
- Powerful Document Search.
- Enable LLMs to search Solr collections using simple or complex queries for instant knowledge retrieval.
- Advanced Filtering & Sorting.
- Use Solr's filtering and sorting capabilities to deliver precise, relevant results to users and agents.
- Asynchronous & Scalable.
- Handle high-volume, concurrent search requests with asynchronous communication and scalable architecture.
- Secure Authentication.
- Protect your Solr data with JWT authentication and configurable security settings.
Direct HTTP API & Tool Endpoints
Configure fast, reliable HTTP access for your Solr-backed MCP server. Expose clear tool and resource endpoints for AI workflows, including advanced search and document retrieval by ID. Integrate with FlowHunt, Claude Desktop, or your custom LLM applications using standard APIs and robust authentication.
- HTTP & MCP Protocol Support.
- Choose between direct HTTP API or MCP protocol for seamless integration and accessibility.
- Tool & Resource Endpoints.
- Expose endpoints for advanced search and document fetching, tailored for LLM and agent workflows.
- Document Retrieval by ID.
- Efficiently retrieve specific Solr documents by ID for streamlined research, support, or automation.
Easy Setup & Scalable Deployment
Get started quickly with Docker-based Solr environments, automated setup scripts, and clear configuration. Scale your deployment from local development to production, with full test coverage and support for custom authentication, logging, and integration with modern AI and RAG platforms.
- Rapid Docker Setup.
- Launch a ready-to-use Solr environment with sample data in minutes using Docker Compose.
- Comprehensive Testing.
- Ensure reliability with a suite of unit and integration tests, and robust CI workflows.
- Flexible Configuration.
- Easily configure connection, authentication, and logging to fit your organization's requirements.
MCP INTEGRATION
Available Solr Search MCP Integration Tools
The following tools are available as part of the Solr Search MCP integration:
- search
Search Solr documents with filtering, sorting, and pagination to find relevant results.
- get_document
Retrieve a specific Solr document by its ID, returning selected fields and metadata.
Connect Your Solr with FlowHunt AI
Connect your Solr to a FlowHunt AI Agent. Book a personalized demo or try FlowHunt free today!
What is MCP-Server for Apache Solr
MCP-Server for Apache Solr is an open-source project that implements a Model Context Protocol (MCP) server designed to provide document search capabilities through Apache Solr. This server acts as a bridge between Large Language Models (LLMs) and Apache Solr, enabling LLMs to perform advanced search, retrieval, filtering, and management of documents stored in Solr collections via a standardized protocol. The solution features asynchronous communication with Solr, type-safe Pydantic interfaces, JWT authentication, and a Docker-based development environment. It supports both MCP and HTTP modes, making it accessible for both AI agent integrations and traditional clients. Its primary use is to empower AI agents and applications to contextually search, retrieve, and manage large collections of documents, making it a valuable asset for enterprises and research teams dealing with significant textual data.
Capabilities
What we can do with MCP-Server for Apache Solr
With the MCP-Server for Apache Solr, users and AI agents can interact programmatically with Solr to unlock powerful document search and management capabilities, all through a standardized protocol interface.
- Search Solr collections
- Execute simple or complex queries to search across Solr indexes.
- Retrieve documents by ID
- Fetch full document details using unique identifiers.
- Advanced filtering and sorting
- Apply filters, sorting, and pagination to refine search results.
- Direct HTTP and MCP access
- Use either MCP protocol or a FastAPI-based HTTP server for flexible integration.
- Automate search tasks
- Enable AI assistants to automate and manage document search workflows seamlessly.
How AI Agents Benefit from MCP-Server for Apache Solr
AI agents benefit from MCP-Server for Apache Solr by gaining structured, scalable, and secure access to vast document repositories. By leveraging the MCP protocol, LLMs can contextually query, filter, sort, and retrieve relevant information in real-time, powering advanced research, automated knowledge extraction, and intelligent content management solutions. The standardized API surface and support for authentication ensure robust integration in enterprise and research settings.