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Cycles — Budget Authority for AI Agents MCP server

by runcycles·io.github.runcycles/cycles-mcp-server·v0.6.1
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Runtime budget authority for AI agents — reserve, enforce, reconcile spend across providers

B82/100grade B
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B82/100

full report

Adoption
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0 stars37 downloads/wk

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Cycles — Budget Authority for AI Agents tools (9, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • cycles_check_balance

    Check current budget balance for a scope. Returns remaining, reserved, spent, allocated, and debt amounts. At least one subject filter (tenant, workspace, app, workflow, agent, or toolset) is required. Do not use as a substitute for cycles_reserve \u2014 balances can change between check and action.

  • cycles_commit

    Commit actual usage after an operation completes. Always call this after cycles_reserve whether the operation succeeded or failed. Finalizes the budget charge and releases any unused reserved amount back to the pool.

  • cycles_create_eventwrite action

    Record a usage event directly without the reserve/commit lifecycle. Use for fire-and-forget metering of completed operations where pre-estimation is not available. The event is applied atomically to all derived scopes.

  • cycles_decide

    Lightweight preflight check \u2014 ask whether an action would be allowed without reserving budget. Does not create a reservation. Use at workflow start to decide strategy. For concurrency-safe budget locking, use cycles_reserve instead.

  • cycles_extend

    Extend the TTL of an active reservation. Use as a heartbeat for long-running operations to prevent the reservation from expiring. Does not change the reserved amount.

  • cycles_get_reservation

    Get details of a specific reservation by ID. Returns status, subject, action, reserved amount, timestamps, and affected scopes. Useful for debugging and monitoring long-running operations.

  • cycles_list_reservations

    List reservations, optionally filtered by status (ACTIVE, COMMITTED, RELEASED, EXPIRED) or subject fields. Useful for debugging stuck reservations or auditing budget usage.

  • cycles_release

    Release a reservation without committing. Use when an operation is cancelled, skipped, or fails before execution. Returns the released budget amount back to the pool.

  • cycles_reserve

    Reserve budget before a costly operation (LLM call, tool invocation, external action). Returns a reservation_id to commit or release later. If decision is not ALLOW, do not proceed with the operation. For lightweight preflight checks without reserving, use cycles_decide instead.

Public scan report

scanner v0.1.9 · 2026-09-24 · same rubric, same numbers if you re-run it

no findings
  • Code scan4 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 0 days ago15/15
  • Maintainer identityregistry namespace matches repository owner7/10
Overall 82/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Cycles — Budget Authority for AI Agents compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
82/100
higher than 63% of 48,255 servers
Tools
9
the typical server has 7
Tools that change things
11%
typical: 0%. Fewer write tools means less an agent can break
Downloads a week
37
more than 28% of 12,191 servers with a package

What its tools let an agent do: 8 read · 1 change

Install Cycles — Budget Authority for AI Agents in Claude Code, Cursor or VS Code

Runs npx -y @runcycles/mcp-server on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add cycles-mcp-server -- npx -y @runcycles/mcp-server
Add to Cursor

What the publisher says

From the Cycles — Budget Authority for AI Agents repository's README, as published. We do not edit it. Read it on GitHub

Cycles MCP Server — AI agent runtime control over Model Context Protocol

MCP server that gives any MCP-compatible AI agent (Claude Code, Cursor, Windsurf, custom agents) runtime budget, action, and audit authority — enforce LLM cost limits, tool call caps, action permissions, and audit trails before execution, with zero agent code changes. Connect via MCP and use the budget tools (cyclesreserve, cyclescommit, cyclesrelease, cyclesdecide) directly from the agent's tool-calling loop. Powered by Cycles. See Security Model & Enforcement Boundary for what is enforced server-side versus cooperatively in the agent loop.

Why use this?

Autonomous AI agents (Claude, GPT, custom agents) call LLMs, invoke tools, and hit external APIs — but have no built-in way to cap how much they spend. A single agent loop can burn through hundreds of dollars before anyone notices. Multiply that across tenants and teams, and cost control becomes a real problem.

This MCP server gives any MCP-compatible agent a runtime budget authority: a set of tools to check, reserve, spend, and release budget before and after every costly operation. The agent asks "can I afford this?" before acting, and reports what it actually used afterward.

Who needs this:

  • Platform teams building multi-tenant agent systems that need per-customer or per-workspace spend limits
  • Agent developers who want agents to self-regulate — degrade to cheaper models when budget is low, skip optional tool calls, reduce retries
  • Enterprises deploying AI agents that need guardrails so a runaway agent can't blow through a budget

Why MCP specifically:

MCP is the standard protocol that AI hosts (Claude Desktop, Claude Code, Cursor, Windsurf, custom agents) use to discover and call tools. By exposing Cycles as an MCP server, any MCP-compatible agent gets budget awareness as a plug-in — just add the server to your config. No SDK integration in the agent's own code required.

The server also ships built-in prompts so an AI assistant can help you design your budget strategy, generate integration code, and diagnose budget overruns — not just enforce budgets at runtime.

Use Cases

Coding agent with a per-task dollar cap

You run a Claude Code agent that writes and iterates on code. Each task should cost no more than $5. The agent calls cyclesreserve before every LLM call with a cost estimate in USDMICROCENTS. If the reservation comes back DENY, the agent stops and reports "budget exhausted" instead of silently racking up charges. When the call completes, cycles_commit records the actual token cost so the running total stays accurate.

Multi-tenant SaaS with per-customer budgets

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Cycles — Budget Authority for AI Agents: common questions

Is Cycles — Budget Authority for AI Agents MCP server safe?
Mostly: it is graded B (82/100). Read the Cycles — Budget Authority for AI Agents safety report
How do I install Cycles — Budget Authority for AI Agents?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Cycles — Budget Authority for AI Agents need an API key?
Yes. The registry entry asks for CYCLES_API_KEY.
Is Cycles — Budget Authority for AI Agents maintained?
The last commit was 41 days ago (2026-09-24). The latest release is v0.6.1.
How does Cycles — Budget Authority for AI Agents compare with other MCP servers?
safety score 82/100 (higher than 63% of 48,255 servers); tools 9 (the typical server has 7); tools that change things 11% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.