Skip to main content
Glama
donliggett

mcp-context-window

doc_ingest

Load large text or files into an external store, issuing a document id for later use. Keeps content on disk so you can page, search, and browse chunks while preserving your context window.

Instructions

Load a large text into the store and split it into addressable chunks. Use this INSTEAD OF reading a big file into your context: the content stays on disk and you page through it with doc_outline, doc_search and doc_window. Accepts inline text, or a file path if the server was started with an ingest root. Returns a document id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoThe content, passed inline
titleNoLabel for the document
doc_idNoReuse a specific id, replacing any document already stored under it
file_pathNoRead from this file instead. Requires --ingest-root to be configured.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral transparency burden and does it well: it reveals the key non-obvious behavior that content stays on disk rather than being loaded into context, and that it is split into addressable chunks. It also discloses the return value (a document id) and the ingest-root requirement. One smaller behavior, doc_id replacement removing existing stored content, is only present in the schema rather than the description, so the transparency is very good but not perfect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Every sentence earns its place: purpose in sentence one, usage guidance and alternatives in sentence two, input modes in sentence three, and the return value in sentence four. The most critical facts are front-loaded, and there is no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a moderately complex tool with no annotations and no output schema, the description covers the full contract an agent needs: what the tool does, why it should be used, what the preconditions are, and what it returns. It also positions the tool within the wider workflow of doc_outline, doc_search and doc_window. Nothing essential for a correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already has 100% description coverage with clear, self-explanatory parameter descriptions, so the structured data is doing most of the work. The description adds a conceptual cross-reference between inline text and file_path as alternative input modes, but this largely restates what the schema already says. Descriptively, it provides little beyond the schema baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific, unambiguous action: 'Load a large text into the store and split it into addressable chunks.' It clearly distinguishes the tool from alternatives by saying it should be used instead of reading a large file into context, and it names the complementary paging tools (doc_outline, doc_search, doc_window). An agent can immediately understand what this tool does and how it fits with its siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use this INSTEAD OF reading a big file into your context' gives an explicit, direct rule for when this tool is the right choice. The description also explains the follow-up workflow, stating content stays on disk and is paged through with doc_outline, doc_search and doc_window, and it clarifies the file_path precondition regarding the ingest root.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/donliggett/mcp-context-sliding'

If you have feedback or need assistance with the MCP directory API, please join our Discord server