tolstoy-mcp
Related Servers
Alternatives to tolstoy-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables Claude to search and read the user's local document collection (PDF, Word, Excel, Markdown, plain text) during a conversation by subject, by file name/path, or by exact word, and to retrieve file contents page by page. It also supports finding folders relevant to a topic and checking indexing status, with everything running locally on the user's machine.MIT
- AlicenseNot gradedqualityCmaintenanceEnables Claude Code to perform local hybrid search over crawled web pages and personal PDF, Markdown, HTML, and text documents, returning cited passages with source, section, page, and score details. It also exposes tools to list documents, retrieve full document text, and check index status.1Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables Claude to query a locally imported collection of PDF, TXT, and MD files via SQLite FTS5 full-text search (including Chinese), and to browse notebooks, source files, and individual passages. Every search result carries traceable citations such as filename, page number, line number, or timestamp.MIT
- AlicenseNot gradedqualityAmaintenanceEnables Claude to search locally indexed exported chat history and project docs, retrieving full messages and conversation IDs via full-text search.1MIT
- AlicenseNot gradedqualityCmaintenanceEnables local RAG-based book and PDF search through Claude Desktop, using hybrid BM25 and vector retrieval with ChromaDB, plus optional OCR for scanned documents.MIT
- FlicenseNot gradedqualityAmaintenanceEnables AI hosts such as Claude Desktop, Cursor, and Cline to search, ask questions of, and receive cited answers from a local hybrid vector-plus-BM25 index built over scattered notes, project docs, PDFs, and chat logs. Exposes 8 tools with resources and prompts so agents can retrieve section-level citations from a personal knowledge base without leaving their own interface.-
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: 'recall' performs hybrid search for fragments by topic, while 'read_document' sequentially reads a full document. An agent can easily tell them apart without overlap.
'read_document' follows a clear verb_noun pattern, but 'recall' is a bare verb without an object, deviating slightly. Both are lowercase and action-oriented, so the set is mostly consistent with minor variation.
Two tools are borderline thin for a corpus server; typical well-scoped sets have 3–15 tools. While search and read cover a basic retrieval loop, additional tools for discovery or metadata could be expected.
The surface allows searching and reading documents, but there is no explicit way to list or browse available documents, nor to retrieve metadata such as dates or titles. This creates a notable gap for agents that need to discover what exists before reading.