Skip to main content
Glama

store

Store and organize project content: save reference documentation, ingest web pages, maintain persistent notes, or register project directories for automated indexing and search.

Instructions

Store content or register a project. Use type "library" (default) to store reference documentation, type "url" to fetch and ingest a web page, type "scratchpad" to save persistent notes/scratch space, or type "project" to register a project directory for file watching and ingestion.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoWhat to store: "library" for reference docs (default), "url" to fetch and ingest a web page, "scratchpad" for persistent notes, "project" to register a project directory
contentNoContent to store (required for type "library")
libraryNameNoLibrary name (required for type "library" unless forProject is true)
forProjectNoWhen true, store to libraries collection scoped to the current project. libraryName becomes optional (defaults to "project-refs").
pathNoProject directory path (required for type "project")
nameNoProject display name (optional for type "project", defaults to directory name)
titleNoContent title (for type "library")
urlNoSource URL (for web content)
filePathNoSource file path
tagsNoTags for scratchpad entries
sourceTypeNoSource type (default: user_input)
metadataNoAdditional metadata
Behavior3/5

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

With no annotations provided, the description carries full burden. It reveals some behavioral traits: it's a write operation ('store', 'register'), mentions persistence ('persistent notes'), and describes different ingestion behaviors (fetching web pages, file watching). However, it doesn't disclose critical details like authentication requirements, rate limits, error conditions, or whether operations are idempotent.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded with the core purpose. Every sentence earns its place by explaining different type options. However, it could be slightly more structured with clearer separation between the four main use cases rather than one long sentence.

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

Completeness3/5

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

Given the tool's complexity (12 parameters, multiple distinct operations) and lack of both annotations and output schema, the description is incomplete. It explains what the tool does but doesn't cover important behavioral aspects like what happens after storage, how to retrieve stored content, error handling, or performance characteristics that would help an agent use it effectively.

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?

Schema description coverage is 100%, so the schema already documents all 12 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it mentions the 'type' parameter options and their purposes, but doesn't explain relationships between parameters or provide additional context not already in the schema descriptions.

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 clearly states the tool's purpose with specific verbs ('store content or register a project') and distinguishes it from siblings by detailing four distinct use cases (library, url, scratchpad, project). It goes beyond a simple restatement of the name by explaining what types of content can be stored.

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

Usage Guidelines4/5

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

The description provides clear context for when to use each type option (e.g., 'use type "library" to store reference documentation'), but doesn't explicitly mention when NOT to use this tool versus alternatives like 'retrieve' or 'search'. It offers good guidance within the tool but lacks sibling comparison.

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/ChrisGVE/workspace-qdrant-mcp'

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