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Langfuse Docs

getLangfuseDocsPage

Fetch the raw Markdown for a single Langfuse docs page. Accepts a docs path (e.g., /docs/observability/overview) or a full https://langfuse.com URL. Returns the exact Markdown (may include front matter). Use when you need a specific page content (Integration, Features, API, etc.) or code samples. Prefer searchLangfuseDocs for broader questions where there is not one specific page about it. Changelog pages (/changelog/...) are historical release notes: use them only to confirm that a feature exists or when it shipped, not as an implementation reference. Their code samples reflect the SDK/API at release time and may be outdated, so for implementation follow the current docs and the API/SDK reference instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathOrUrlYesDocs path starting with "/" (e.g., /docs/observability/overview) or a full URL on https://langfuse.com. Do not include anchors (#...) or queries (?foo=bar) — they will be ignored.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns exact Markdown possibly including front matter, that anchors and query strings are ignored, and warns that changelog code samples may be outdated. This gives the agent a clear behavioral model of what the tool does and its limitations.

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?

The description is well-structured and front-loaded with the core purpose, then input formats, then usage guidance, and finally the changelog caveat. Every sentence adds value, and while it is relatively long, it is dense with actionable information and free of filler.

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 single-parameter tool with no output schema, the description fully covers what the agent needs: accepted inputs, what is returned, when to use it versus alternatives, and caveats about changelog pages. Nothing essential is missing for correct invocation.

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

Parameters5/5

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

Although the schema already documents the pathOrUrl parameter with 100% coverage, the description adds extra meaning by explicitly stating anchors (#...) and queries (?foo=bar) will be ignored, and clarifies accepted formats (path or full URL). This goes beyond the schema's basic type description.

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 fetches raw Markdown for a single Langfuse docs page, specifies accepted input formats (path or full URL), and distinguishes itself from searchLangfuseDocs by noting when to prefer that sibling for broader questions. This precisely differentiates it from 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?

Explicitly instructs to prefer searchLangfuseDocs for broader questions, and provides detailed guidance on changelog pages: they are historical release notes, to be used only to confirm existence or release timing, not as implementation reference. This is clear when-to-use and when-not-to-use guidance with alternatives named.

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

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