Skip to main content
Glama
seedfast-ai

Seedfast MCP Server

Official

seedfast_run_answer

Answers a pending Seedfast run question: approve the proposed plan as-is or supply a refinement to adjust scope, then the run resumes.

Instructions

Answers a pending question for a run that is in state 'awaiting_input'. The CLI forwards backend questions (scope validation issues, replans) to this MCP server via subprocess stdio and blocks for up to 5 minutes on a reply. Call this tool with the runId, the questionId from seedfast_run_status (or the seedfast://runs/{runId}/pending_question resource), and an answer object. Set answer.human_answer=true to approve the current plan/scope as-is; set human_answer=false and supply answer.raw with a textual refinement (e.g., 'seed only the org schema') when the plan should be adjusted. Returns a short text confirmation. On success the run transitions back to 'running'; poll seedfast_run_status to observe progress. Does not require SEEDFAST_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYesRun ID returned by seedfast_run (the run must be in state 'awaiting_input').
answerYesAnswer payload: set human_answer=true to approve, otherwise provide refined scope in raw.
questionIdYesQuestion ID from the pending_question resource or from seedfast_run_status output.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.6.4

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: it explains the CLI blocks up to 5 minutes, the run transitions back to 'running' on success, returns a short text confirmation, and does not require SEEDFAST_API_KEY. It also explains the human_answer true/false behavioral distinction, which is beyond the schema.

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 appropriately detailed for a tool with a nested object parameter and no annotations, and it is front-loaded with the core purpose. Every sentence adds useful information: source of IDs, answer semantics, blocking behavior, state transition, return value, and auth requirement. No 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?

Given the nested answer object, absence of annotations, and absence of an output schema, the description is remarkably complete. It covers all required inputs, exact answer-flag semantics, expected return, post-success behavior, how to observe progress, and auth. 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.

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context on top: runId must come from a run in 'awaiting_input', questionId is sourced from seedfast_run_status or the pending_question resource, and answer.raw is illustrated with a concrete example. This justifies above 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 states a specific action ('Answers a pending question') with an explicit precondition (run state 'awaiting_input'), and clearly situates it among siblings as the tool for responding to backend questions. No ambiguity exists about what resource it operates on or why it differs from run_cancel, run_status, or the plan tools.

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?

It gives clear when-to-use context: the run must be in 'awaiting_input', and questionId should come from seedfast_run_status or the pending_question resource. It does not explicitly name alternative tools or state when-not-to-use, but the conditional context is strong enough for correct selection.

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