plith

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as ai.plith/plith and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 28 Jul 2026. Not supplied by the maker.

• dedupq_check

  Before executing any LLM task, check if an identical or semantically similar task has already been completed. Returns cached result on hit, saving one LLM call. On a miss, execute your task and call d

• dedupq_complete

  After executing a task, store the result so future identical or similar tasks return a cache hit via dedupq_check. Costs 2 credits.

• burnrate_estimate

  Before executing a multi-step agent plan, estimate the total LLM cost. Returns per-step breakdown and optimization suggestions. If the estimate exceeds your budget, pipe the same plan into burnrate_op

• burnrate_track

  Log the actual cost of an LLM call after execution. Call this after every LLM request to build calibration data that improves burnrate_estimate accuracy over time. Free — no credits charged. Returns t

• burnrate_optimize

  Get a cheaper equivalent plan by substituting models with lower-cost alternatives. Call after burnrate_estimate if the estimated cost exceeds your budget. Returns the optimized plan with substituted m

• burnrate_budget

  Get today's tracked LLM spend, per-model breakdown, projection, and budget alerts. Free — no credits charged.

• qualitygate_validate

  After your agent generates output, validate it against your rules before shipping. Runs deterministic checks (regex, JSON schema, syntax) plus optional LLM-powered tone and factual analysis. Returns a

• guardrail_check

  Evaluate a proposed agent action against your governance policies. Returns allow or deny with the matched policy reason. Requires at least one active policy created via guardrail_create_policy. Determ

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