fetch_pageReturn the full extracted text of a page already in the index. This serves stored content and does not hit the live site, so it is fast and cannot be blocked. Use it after search to read a result.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of an indexed page. | |
| maxChars | No | Truncate the body to this many characters. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, and the description adds meaningful behavioral details: it is fast, cannot be blocked, and serves stored content rather than hitting the live site. The word 'full' is slightly at odds with maxChars truncation, but the schema clarifies that behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three tight sentences: first states the core function, second gives the key behavioral trait, third gives the usage context. No filler or redundant restating of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with readOnlyHint, the description covers the main usage, the stored-content behavior, and the workflow position. It does not describe error behavior for missing pages or explicitly mention truncation, but the schema covers maxChars and the description provides enough context to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both url and maxChars are already clearly documented in the schema. The description restates that the url must be an indexed page, but adds little meaning beyond the existing parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Return'), resource ('full extracted text of a page already in the index'), and scope. The distinction from live-site fetching and the mention of serving stored content set it apart from fetch_pages and search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use it after search to read a result, giving a clear workflow context. It also clarifies that it serves stored content and does not hit the live site, though it does not name alternative tools for cases such as needing fresh data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation: core search, batch search, product search, passage-level retrieval, similarity lookup, page fetching, watch management, and index introspection. The potentially overlapping tools are explicitly differentiated, such as search_products versus search, and the batch variants are clearly scoped.
Most tools follow a clear verb_noun snake_case pattern like fetch_page, delete_watch, list_sites, and watch_query. The pattern is slightly weakened by noun-phrase names like index_stats and source_profile, but the naming remains predictable overall.
Fourteen tools is within the ideal range for a search-focused server, and each tool covers a distinct feature: search, batch retrieval, product search, passage extraction, similarity, full-text fetching, watch lifecycle, and corpus introspection. No tool feels redundant or extraneous.
The toolset covers the full agent workflow for web search: querying, reading indexed pages, extracting citable passages, finding related content, monitoring with watches, and understanding corpus coverage and source trustworthiness. Minor conveniences like updating a watch are absent, but the lifecycle is otherwise complete.