"Resources for Personal Finance and Budget Management" matching MCP servers:

A comprehensive MCP server for managing personal finances, enabling users to track expenses, manage budgets, monitor financial goals, and analyze spending patterns through an AI assistant. All data is stored locally in SQLite for complete privacy.

A lightweight MCP server for tracking personal expenses, income, and budget summaries using SQLite.

Enables Claude to analyze personal finances by reading bank CSVs or connecting to Plaid for live transactions, categorizing spending, flagging overspending against benchmarks, and generating actionable reports and savings tips.

Enables local-first personal finance management through deterministic tools for importing, categorizing, and analyzing bank transactions.

MCP server scaffold for budget tooling, currently only provides a placeholder ping tool returning 'pong' to confirm plumbing works. No real budget functionality yet.

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

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

MCP server for estimating LLM token consumption and costs from project documents, code, and materials. Provides 8 tools including project budget planning, token/cost estimation, GitHub repo analysis, and pricing refresh.

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.

Personal finance MCP server that integrates Plaid bank data with local SQLite memory for conversational budgeting, goal tracking, and transaction management.

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

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

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 that lets you log and query your own spending through natural conversation with Claude, instead of a spreadsheet or app.

A read-only personal finance MCP server for analyzing transaction CSVs, providing tools to filter transactions, summarize spending, categorize charges, and flag unusual activity.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

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.

Enables a Claude Code agent to fetch remaining 5-hour and weekly subscription usage limits, reset times, and per-window breakdowns as JSON. It provides the same figures as /usage through a local, read-only tool.

A personal finance tracker MCP server that imports Rocket Money data or connects banks via SimpleFIN to a local SQLite database, enabling Claude to analyze spending, subscriptions, cash flow, and debt payoff with complete privacy.