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TokenOracle MCP

Token Oracle is a Model Context Protocol (MCP) server that estimates, compares, and controls LLM API costs before agents spend tokens. It exposes nine tools, four read-only Resources, and a cost_analysis_workflow Prompt template. It uses a proprietary pricing algorithm without a backing LLM to ensure deterministic budget workflows.

Designed to work with agent swarms backing one or zero employee companies, Token Oracle acts as a tiny CFO within your OpenClaw swarm keeping spend down and making suggestions to improve promptings.

Save them tokens, call Token Oracle today!

MCP tools exposed:

• estimate_cost — Estimates the USD cost of a single LLM API call before execution. Input: task_description, prompt_text, task_type, or explicit token_count. Output: cost_usd, recommended_model, confidence, will_fit_context, pricing_updated. Annotations: readOnlyHint:true, idempotentHint:true, openWorldHint:false.
• estimate_cost_batch — Prices up to 100 LLM tasks in a single call. Returns per-task breakdown, total_cost_usd, and cheapest_model_for_all. Use before starting any multi-step pipeline.
• compare_models — Ranks LLM pricing across all supported providers for a given task. Returns models sorted by cost with speed_tier and quality_tier. Supports filtering by min_quality, max_cost_usd, and provider. Input: task_type, token_count, or prompt_text.
• budget_check — Checks whether a planned task fits within a monthly budget. Returns can_proceed (boolean), remaining_budget_usd, budget_consumed_pct, and cheaper_alternatives with savings_pct. Input: monthly_budget_usd, current_spend_usd, and task description.
• find_cheapest_for_budget — Inverse of budget_check. Given a budget_usd cap and task, returns the best model/quality combination within budget plus all alternatives ranked by quality then cost.

MCP Resources exposed:

• token-oracle://meta — Machine-readable server capability document (version, model_count, pricing metadata)
• token-oracle://models — Model IDs with metadata for discovery and validation
• token-oracle://heuristics — Task-type token heuristics and keyword classifier patterns (auditable)
• token-oracle://pricing/changelog — Append-only log of pricing changes; use to detect pricing updates over time

MCP Prompt exposed:

• cost_analysis_workflow — Guided three-step prompt template: estimate_cost → compare_models → budget_check. Arguments: task_description, monthly_budget_usd (optional), quality_threshold (optional).

Supported providers: Anthropic, OpenAI, Google, Groq, Together AI, Mistral, DeepSeek, Cohere (100+ models).

Canonical agent workflow example: Goal: Run 500 product description generation tasks. Budget $50/mo, current spend $43.

1. estimate_cost_batch({ tasks: [{ task_type: "generate", token_count: { input: 200, output: 800 }, quantity: 500 }] }) → total_cost_usd: $0.60
2. compare_models({ token_count: { input: 200, output: 800 }, task_type: "generate", min_quality: "med", max_cost_usd: 0.002 }) → deepseek-v3 at $0.00035/task ($0.175 total) — 71% cheaper, same quality tier
3. budget_check({ monthly_budget_usd: 50, current_spend_usd: 43, token_count: { input: 200, output: 800 }, model: "deepseek-v3" }) → can_proceed: true, remaining: $6.825, budget_consumed_pct: 2.4% Decision: Use deepseek-v3. Save $0.425 vs gpt-4o-mini.

Pricing:

• Free: 1000 API calls/day, all hosted tools via the remote endpoint, no credit card
• Pro ($29/mo): Unlimited calls, track_spend tool (persisted cost ledger per API key), priority throughput, spend attribution per agent/task/session

Contact: info@guffeyholdings.com

Hosted endpoint

• Canonical remote MCP URL: https://mcp.guffeyholdings.com/TokenOracle
• Canonical MCP name: com.guffeyholdings/token-oracle

Direct remote configuration:

{
  "mcpServers": {
    "token-oracle": {
      "type": "streamable-http",
      "url": "https://mcp.guffeyho

... [View full README on GitHub](https://github.com/VictoryInTech/TokenOracle-MCP#readme)