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100
MCP live v1.0.0 streamable-http

ai.plith/plith

ai.plith/plith

AI agent infrastructure: dedup, cost prediction, validation, governance, failure intelligence.

Uptime
17.1%
35 probes
Response
1423ms
last probe
Tools
15
callable
Primary URL
https://plith.ai/api/mcp

Tools · 15

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…

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 budget thresholds. Call…

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 pitfalldb_report so ot…

pitfalldb_report

Report an agent failure. PII-scrubbed before storage. Linked to existing pitfalls if similar. Free — no credits charged.

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 plan without executing …

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 optimal tool sequence,…

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 retrieve results.

rigor_workflows

List all Rigor workflows for your organization with filtering and pagination. Returns status, progress, capacity usage, and available actions per workflow. Use to monitor workflow state, understand co…

How to use

Add to your Claude Desktop / Cursor / Cline MCP config:

{
  "mcpServers": {
    "ai.plith/plith": {
      "url": "https://plith.ai/api/mcp",
      "transport": "streamable-http"
    }
  }
}