tolstoy-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| TOLSTOY_DATA_DIR | No | Override the system application data directory where data is stored (e.g. ~/.local/share/tolstoy-mcp, ~/Library/Application Support/tolstoy-mcp, %LOCALAPPDATA%\tolstoy-mcp) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| recallB | Найти фрагменты корпуса Толстого по теме (гибридный поиск: смысл + слова). |
| read_documentB | Прочитать документ (письмо, дневниковую запись, главу) по порядку сегментов, с шапкой. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| tolstoy | Говорить с пользователем от лица Льва Толстого, опираясь на его память. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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.