"Actual Budget" matching MCP servers:

An MCP server that connects Actual Budget to Claude, enabling users to manage budgets, transactions, and spending insights through natural language.

MCP server for integrating Actual Budget with Claude and other LLM assistants.

Keyword Metrics for Google Ads search volume, CPC, advertising competition and monthly history. Optional AI Search Volume provides modeled question-demand signals, not actual ChatGPT or Perplexity query counts. Free discovery and quotes; paid calls require an approved budget and use USDC on Base via x402. Also includes SERP, domain and local-market research.

Budget Planner AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Provides structured access to Swedish national budget data, including allocations, tax revenue, and fiscal data. Enables queries on budget overviews, expenditure areas, revenue timeseries, and voting results via MCP tools.

Enables autonomous agents to enforce financial guardrails by tracking real-time token burn and cost velocity, automatically throttling or freezing execution when budgets are exceeded. It also blocks destructive shell commands, prompt injections, and runaway planning loops while sanitizing outputs before they are returned.

Manages token budgets for AI agents, enabling tracking and enforcement of usage limits with built-in EU AI Act compliance.

Enables agents to monitor running loops, estimate token consumption and monetary cost, prune verbose thinking chains near limits, and route sub-tasks between fast/cheap models and deep reasoning engines. It provides budget-aware model routing and telemetry through MCP.

Enables calculating PagedAttention KV cache allocation and GPU memory budgets for vLLM-style chunked prefill workloads via MCP.

Compiler introspection for the Hirð language (typed actors and effect rows on the BEAM): type inference, definition lookup, effect-row explanation, IR fragments, actor protocol and supervision graphs, and token-budget-aware symbol summaries.

Multi-agent swarm orchestrator for AI workflows. Exposes blackboard read/write, agent dispatch, permission gating (AuthGuardian), token budget enforcement (FederatedBudget), and audit log tools over MCP. Supports 14 AI framework adapters including LangChain, AutoGen, CrewAI, Codex, and A2A — mix any frameworks in one swarm with race-condition-safe shared state.(Traffic light for agents)

A budget-bound x402 payment wallet for AI agents: it autonomously pays HTTP 402 payment-gated URLs across every major chain (EVM, Solana, and many non-EVM families). Self-custodial and backendless, your key, your RPC, with spend caps enforced before any on-chain send.

Enables AI agents to call paid APIs and settle HTTP 402 payment challenges with USDC on Base, without private keys ever being involved.

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.

Flight price search via the Aviasales / Travelpayouts Data API: 13 read-only tools for fares by route and month, cheapest day, flexible dates, budget search and IATA lookup.

Analyzes all permission settings files for coding agents, showing which settings take precedence and identifying rules that are accepted but ignored. Helps users understand and debug their agent's actual permission behavior.

Budget, approval, and receipt layer that agents call when they buy on a human's behalf. MCP server with dry-run by default.

AgentGuard47 is runtime safety infrastructure for AI agents. It adds budget caps, loop detection, retry limits, timeouts, local traces, and incident reports so agents can stop bad runs while they are happening, not just explain them afterward.

Lets an AI agent read a YNAB budget and ask plain-language questions about it — where money went, what still needs a category, whether an account matches the bank, and when money would run out. Changes such as categorising, splitting or budgeting are read-only by default, and every write is previewed, explicitly confirmed, and undoable.

macOS automation for AI assistants: 17 typed tools for window management, application menus, keyboard input, clipboard, browser tabs, screenshots, displays and Apple Shortcuts, driven through AppleScript and JXA. Menu clicks are self-correcting — a wrong item returns the actual menu contents so the model can retry with the right one.