"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.

Enables LLMs to interact with a self-hosted Actual Budget instance, providing financial data and management tools with correct financial semantics and no cents math.

Enables AI assistants to interact with Actual Budget for personal finance management through natural language, supporting transactions, account balances, budget tracking, spending analysis, and payment searches.

An MCP server for Actual Budget that connects to your Actual sync server, opens one budget file, and exposes it to MCP clients over streamable HTTP or stdio.

Enables agents to read and edit budgets in Actual Budget via natural language, with a safety layer that requires confirmation for destructive actions.

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

Provides a read-only interface to YNAB budget data, allowing AI assistants to inspect budgets, accounts, categories, transactions, and more. Includes an experimental guarded write workflow for category assignments.

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).

An interactive tool for visualizing and managing budget allocations across business categories with real-time charts and industry benchmarks. It allows users to adjust spending distributions and compare them against historical trends and startup stage data.

Model-agnostic code memory MCP server using budget-aware graph retrieval for AI agents, providing sub-millisecond queries, token budgeting, and deterministic results without embeddings or vector databases.

Enables auditing MCP servers' tools by their estimated context token cost, ranking verbose names, descriptions, and schemas before they consume the agent window. Can run as an MCP tool so agents can budget their own context.

An MCP server for Actual Budget that enables AI agents to read and manage budget data, including accounts, transactions, categories, payees, and budget envelopes, via a long-lived engine singleton.

Enables budget management, scenario creation, and value updates through natural language, integrating with the Budget Planner MVP.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

Drop-in stdio interceptor that gates MCP tools/call requests through a YAML policy (block / require_approval / audit / budget cap) before they reach the real server. The same policy file is reused by @jamjet/claude-code-hook and @jamjet/openai-guardrail, so one rule set covers Claude Desktop, Cursor, OpenAI Agents, and custom clients.

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.

Enables AI coding agents to list, read, create, update, delete, and render PlantUML and Mermaid diagrams, and check them against the actual codebase to detect architecture drift.

MCP server for programmatic read-only access to RiseUp cashflow data, allowing AI assistants to retrieve budget information via natural language.

Lets an AI agent hire and pay a verified human: post real-world tasks (voice, observation, judgment) and pay in USDC via a non-custodial x402 auth-capture escrow on Base, budget frozen at deploy. Humans verify their X identity before submitting.

A local, read-only stdio MCP server that lets a Grok Build CLI agent check how much of its weekly SuperGrok / Grok Build usage pool is left, when the period resets, and its Extra Usage cap via tools like get_budget. It reads the existing grok login session and returns per-product figures as JSON, mirroring the TUI /usage screen, so agents can pause before expensive work when quota runs low.