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MCP serverai.plith/plith

AI agent infrastructure: dedup, cost prediction, validation, governance, failure intelligence.
UNRATEDActivestreamable-httpplith.ai

Overview

Score?
UNRATED 0.681
of what a free look can see, on 32 looks
Looks
36
last 12 hr ago
Tools
15
changed 27 days ago

More info

URL
plith.ai/api/mcp
streamable-http
Says it is
plith 1.0.0
protocol 2024-11-05
In the record since
32 days ago

Among servers18,413 with a card

0median 0.606 · this server 0.681 · highest on record 0.8561

Toolsfrom sha256:57e3fe4780…ac1ff2 · +0 −0 27 days ago

The tools this server lists, read out of the definition it returned
ToolSchema
burnrate_budget
Get today's tracked LLM spend, per-model breakdown, projection, and budget alerts. Free — no credits charged.
input · output
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 p
input · output
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 pla
input · output
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 credit
input · output
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
input · output
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.
input · output
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_c
input · output
guardrail_create_policy
Create a persistent governance policy that guardrail_check evaluates on every subsequent call. Define rules using and/or/not operators over action types, resource patterns, and bud
input · output
pitfalldb_query
Check for known failure patterns before executing a task type. Returns pitfalls with severity, fix suggestions, and confidence scores. After your agent runs, submit failures via pi
input · output
pitfalldb_report
Report an agent failure. PII-scrubbed before storage. Linked to existing pitfalls if similar. Free — no credits charged.
input · output
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
input · output
rigor_execute
Execute a structured workflow end-to-end. Call rigor_plan first (free) to preview the step sequence and cost estimate before committing credits. Classifies the task, selects the op
input · output
rigor_plan
Before executing a complex task, get a structured workflow plan with per-step cost estimates. Classifies your task, selects the optimal framework sequence, and returns the full pla
input · output
rigor_status
Check the status of a running or completed Rigor workflow. Returns progress, step results, and the full deliverable when complete. Use after rigor_execute with polling delivery to
input · output
rigor_workflows
List and search Rigor workflows for your organization, with filtering and pagination. Returns status, progress, capacity usage, and available actions per workflow. Use to monitor w
input · output
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