"Actual Budget" matching MCP servers:

Budget management and cost tracking MCP server for autonomous agents, enabling budget creation, cost recording, spending projections, and alert rules.

Manages agentic workflow spend through budget quotes, policy gates, approvals, receipts, and cost evidence exports.

Pay-per-call USDC payment proxy for AI agents. Issue scoped Pay Tokens with hard spending caps and auto-journal every charge to freee / Money Forward / QuickBooks.

Provides constraint satisfaction and optimization capabilities to LLMs and AI agents for scheduling, resource allocation, routing, budget optimization, and configuration problems using Google OR-Tools CP-SAT solver.

MCP server for priority-weighted token budget management in multi-agent LLM systems, enabling dynamic reallocation of unused tokens between agents based on priority and current spend.

Runtime budget authority for autonomous agents - a set of tools to check, reserve, spend, and release budget before and after every costly, risky operation. The agent asks "can I afford this?" before acting, and reports what it actually used afterward.

Enables Claude Code to delegate bounded repository tasks to DeepSeek as a local sub-agent, handling exploration, routine changes, and test runs within a controlled workspace and budget.

Allows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns.

Enables verification of AI coding agent self-reports against git diff truth and a deterministic gate, producing pass/regenerate/reject directives to ensure claimed work matches actual changes.

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

AI payment guardrails for Python & MCP: spend-capped agent identity (KYA), dry-run/budget/approval gates, prompt-injection defense, encrypted secret vault.

Enables agents to discover, suggest, bind, and read local SKILL.md skills via MCP, while enforcing a maximum of three bound skills and a token budget to keep context small.

Enables agents to autonomously pay x402 API requests in USDG on Robinhood Chain while enforcing budget caps and scoped sessions.

Enables AI agents to take real professional decision cases, search reference libraries and rulebooks, submit a decision, and receive an exact score against the professional's actual outcome.

Autonomous financial policy engine and budget guard for AI agent fleets. It verifies payment payloads, velocity caps, escrow release terms, and slippage inflation, returning risk verdicts and signed attestations.

Enables AI coding agents to set budgets per task, check costs before expensive operations, and halt when budget is exhausted, with support for calibration and cloud sync.

Budget & cost control for AI agents: hard per-agent spend caps, rate limits, idempotency, and human-in-the-loop approval — enforced before each LLM call, not after the invoice. One hosted MCP endpoint (no proxy or self-hosting), settled via x402 (USDC on Base).

Enables AI coding agents to self-assign, coordinate, review, and ship work through GitHub Projects v2, with AI-powered PRD generation, sprint planning, issue triage, and token-budget enforcement.

An MCP server that provides tools to audit AI-agent marketplace integrity by scanning listings for deceptive patterns like fabricated engagement, automated seeding, self-advertisement, unpaid work risk, and high-budget bait.

Enables agents to scout open Gibwork bounties, plan subtask crews, preview escrow funding, and inspect subtask status and ledgers without spending money. Read-only tooling keeps all actual escrow funding and fee payment in the CLI under explicit approval.