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Alternatives to opensolr-mcp

  • A
    license
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    An MCP server that indexes documents and serves relevant context to LLMs via Retrieval Augmented Generation (RAG).
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  • A
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    A Python server that enables AI assistants to perform hybrid search queries against Apache Solr indexes through the Model Context Protocol, combining keyword precision with vector-based semantic understanding.
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  • F
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    A CLI tool and MCP server that turns markdown documentation into a searchable, queryable knowledge base.
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Related Servers

  • A
    license
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    quality
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    Enables document ingestion, semantic search, and retrieval-augmented generation via MCP tools and REST API, using vector embeddings and intelligent chunking.
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  • F
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    Enables hybrid vector and keyword search over Azure AI Search indexes via an MCP tool, supporting query with embedding generation.
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  • F
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    Enables users to ingest documents, run retrieval-augmented queries with dense/sparse search and reranking, and inspect ingestion/query traces and evaluation results through MCP tools.
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  • F
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    Provides RAG-based knowledge retrieval and document management as MCP tools, supporting hybrid search, reranking, and retrieval process visualization.
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  • A
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    Enables self-hosted ingestion of arbitrary documents with local chunking and embedding, plus explainable hybrid vector and lexical search over REST and MCP. Provides read-only MCP tools for searching documents, retrieving chunks, and listing collections.
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TDQS

A3.9/5.0

Scored across 10 tools

Disambiguation5/5

Each tool targets a distinct operation: text search, image search, RAG answering, index listing/info, ingestion lifecycle, deletion, and creation. Even the two search variants are clearly separated by query type, and the supporting region/status tools have unambiguous roles.

Naming Consistency4/5

All tools share the opensolr_ prefix and generally follow a verb_noun pattern, but a few names like opensolr_index_info, opensolr_ai_answer, opensolr_ingest_status, and opensolr_vector_regions are noun-style rather than verb-first. The convention is still predictable and readable.

Tool Count5/5

Ten tools cover the primary surface of an Opensolr search server: searching, ingesting, managing documents, and managing indexes. The count feels appropriately scoped without redundant or excessive entries.

Completeness4/5

Core workflows are well covered: create/list/inspect indexes, ingest and check status, delete documents, search by text or image, and get grounded answers. Minor gaps exist, such as no delete_index operation and no explicit index settings update or single-document fetch, but these are not fatal to typical usage.

Maintenance

ActivityMaintained
ResponsivenessNo issues