"Actual Budget" matching MCP servers:

An MCP server that lets AI assistants discover and retrieve official statistics from SDMX services, returning actual data observations rather than just query URLs.

Enables MCP-capable agents to inspect a local Synthesizer installation, query local grids and APIs, find examples, plot grid spectra, and validate scripts, so answers are grounded in the user's actual environment.

MCP server to ask research questions about real-world datasets and get actual database records back, with auto-registration and trial credit.

Provides an MCP server for querying a dataset of 350 Indian startups' marketing channels by stage, sector, and budget, enabling evidence-based channel selection through natural language.

Enables users to search Korean local government project, plan, and budget documents through AI apps, compare cases across municipalities, and check planning, budget, and support conditions against original-source citations.

MCP server for the WhatsMyBudget Analytics API, providing tools to query budget periods, categories, accounts, and summaries.

An MCP server that provides league-accurate fantasy football advice by scoring projections against your Sleeper league's actual scoring settings and roster shape, answering draft, trade, waiver, and lineup questions.

Screens quantum computing POC proposals using expert decision rules to produce auditable triage verdicts before escalation, budget allocation, or specialist routing.

MCP server for semantic research: search arXiv, fetch papers, and answer questions grounded in the actual paper text via RAG tools, resources, and prompts.

Enables AI clients to query raw NEXRAD Level II dual-pol radar data at any point, decoding actual volume data for detailed analysis like reflectivity, velocity, and correlation coefficient.

Enables MCP clients such as Claude, Codex, and Cursor to retrieve Wordstat frequencies, keyword tails, competition data, and Mega-tool reports, and to build or expand semantic cores with budget-capped paid calls and pre-call cost estimates.

MCP server that enables intelligent analysis of legal spend data across multiple sources (LegalTracker, databases, CSV/Excel files), providing features like spend summaries, vendor performance analysis, and budget comparisons.

Enables AI-driven expense tracking and budget management, including adding expenses, setting budgets, analyzing trends, forecasting, and managing savings goals via natural language.

Enables auditing of every citation in a LaTeX or Markdown manuscript (English or Portuguese) against the actual passage in the cited PDF, verifying quotes literally, fetching sources from local folders, Zotero, arXiv and open-access APIs, and flagging bibliography problems such as retractions or missing DOIs. It also drafts and safely applies approved rewrites or new evidence-backed paragraphs in the .tex file with validation, encoding preservation and backups.

Webhound is a research engine with an explicit effort control: a prompt defines the investigation and a dollar budget defines how much work it deserves. It returns cited reports or sourced datasets with the working documents, claims, sources, limitations, and evidence pack behind the answer.