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avivsinai

langfuse-mcp

fetch_trace

Retrieve a single trace by ID with optional observation details and adjustable output format for debugging LLM application performance.

Instructions

Get a single trace by ID with full details.

Args:
    ctx: Context object containing lifespan context with Langfuse client
    trace_id: The ID of the trace to fetch (unique identifier string)
    include_observations: If True, fetch and include the full observation objects instead of just IDs.
        Use this when you need access to system prompts, model parameters, or other details stored
        within observations. Significantly increases response time but provides complete data.
    output_mode: Controls the output format and detail level

Returns:
    One of the following based on output_mode:
    - For 'compact' and 'full_json_file': A response dictionary with the structure:
      {
          "data": Single trace object,
          "metadata": {
              "file_path": Path to saved file (only for full_json_file mode),
              "file_info": File save details (only for full_json_file mode)
          }
      }
    - For 'full_json_string': A string containing the full JSON response

Usage Tips:
    - For quick browsing: use include_observations=False with output_mode="compact"
    - For full data but viewable in responses: use include_observations=True with output_mode="compact"
    - For complete data dumps: use include_observations=True with output_mode="full_json_file"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trace_idYesThe ID of the trace to fetch (unique identifier string)
include_observationsNoIf True, fetch and include the full observation objects instead of just IDs. Use this when you need access to system prompts, model parameters, or other details stored within observations. Significantly increases response time but provides complete data. Pairs well with output_mode='full_json_file' for complete dumps.
output_modeNoControls the output format and action. 'compact' (default): Returns a summarized JSON object optimized for direct agent consumption. 'full_json_string': Returns the complete, raw JSON data serialized as a string. 'full_json_file': Returns a summarized JSON object AND saves the complete data to a file.compact

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description carries full burden. It discloses that include_observations significantly increases response time, explains the output_mode behaviors (compact, full_json_string, full_json_file), and outlines the return structure. It does not cover error handling or auth requirements, but the behavioral context is strong.

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 well-structured with sections (summary, Args, Returns, Usage Tips) and front-loads purpose. While slightly verbose, each sentence contributes meaningful information, earning its place.

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

Completeness4/5

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

Given the tool's complexity (3 params, output schema exists, no annotations), the description covers the return formats for each output_mode and provides usage tips. Missing details on error scenarios or trace existence checks, but overall adequate for a fetch tool.

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

Parameters4/5

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

With 100% schema description coverage, baseline is 3. The description adds value by expanding on the purpose of each output_mode and noting that include_observations pairs well with output_mode='full_json_file' for complete dumps, which goes beyond the schema definitions.

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 starts with 'Get a single trace by ID with full details', clearly identifying the action and resource. The tool name 'fetch_trace' contrasts with plural siblings like 'fetch_traces' and related tools like 'fetch_observation', making its unique purpose evident.

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 'Usage Tips' section provides explicit guidance on when to use each configuration (e.g., for quick browsing use include_observations=False and output_mode='compact'). However, it does not explicitly state when this tool is not appropriate or suggest alternative tools for different use cases.

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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