"Answer" matching MCP servers:

Enables an AI agent to verify its draft answer against supplied sources sentence by sentence, flagging unsupported figures, dates, citations, and must/may wording and offering source-backed corrections. An optional judge mode can additionally assess prose via a configured LLM endpoint, while default operation is deterministic and offline.

Enables checking AI-drafted answers to US retirement-account questions, flagging wrong facts, personal recommendations, and promissory claims with IRS or FINRA sources before they reach customers.

Enables AI assistants to answer British Columbia employment law questions — overtime, breaks, statutory holidays, pay, leaves and termination — from the current official text on BC Laws, in English or Chinese, with the act, section number, link and official "current to" date. Exposes tools to locate acts, browse a table of contents, retrieve and search sections, and map everyday or Chinese terms to the wording the statute actually uses.

Enables Claude to search a local knowledge base covering the Dutch collective labour agreement for temporary agency workers and its surrounding regulations, returning relevant passages labelled as currently valid, historical, or open questions. Every answer cites its source—the law, the cao text, or the body that sets the amount—so outdated rules are never presented as current.

Enables AI agents to query China's GB/T 47746—2026 customer-service compliance standard, providing clause-referenced answers, self-check lists, and standard metadata via MCP tools.

A local MCP server that enables Claude to answer Norwegian tax questions with actual calculations, covering income, wealth, stocks, funds, real estate, crypto, and more.

attendance-engine-mcp is a Model Context Protocol server that gives AI agents deterministic, fixture-backed tools for workforce attendance and wage-and-hour compliance. Built on @attendance-engine/core — a pure-function, zero-deps, 100%-covered TypeScript engine — it lets Claude, Cursor, Windsurf, or any MCP host correctly answer the questions HR/payroll teams actually ask: did this person clock i

Enables users to query EU Carbon Border Adjustment Mechanism data offline: whether a Combined Nomenclature code is in scope, which default emission values apply for a given country of origin, and what the code describes. Every answer cites the legally binding act, the dated data version, and flags that the data itself is not legally binding.

Enables AI assistants to answer questions offline, with no dependencies, about Gulf cyber incident notification duties, including which authorities to alert, their deadlines, and the official source behind each one.

Enables users to look up and search Australian SMSF rules — contribution caps, total super balance and Division 296 thresholds, pension minimums and lodgment deadlines — and to compute contribution headroom, every answer carrying an ato.gov.au or legislation.gov.au citation. It is read-only and deterministic, with no model calls or network access at call time.

Exact French real-estate legal calculations for AI agents: IRL rent revision, service-charge reconciliation, compliant rent receipts — legal basis included in every answer.

Enables AI assistants to answer tax compliance questions (VAT, sales tax, GST) and validate EU VAT numbers in real time via the VIES registry.

Enables agents to query China's GB/T 47746—2026 AI customer-service compliance standard through five clause-level tools — question listing, keyword search, full cited answers, enterprise self-check lists, and standard metadata — over a public read-only streamable-http endpoint with no API key required. Answers include clause sources so compliance questions like mandatory human-handoff scenarios can be resolved without manually paging through the 40-page standard.

Computes Japanese payroll, social insurance, and labour law obligations—such as premiums, withholding tax, and minimum wage—citing the statute each answer relies on, enabling auditable calculations through an AI assistant.

Enables agents to answer questions about Thailand's Personal Data Protection Act by combining hybrid dense/sparse vector retrieval with knowledge-graph traversal over a 190-node graph of the statute's 96 sections. Exposes tools for hybrid section search, related-section lookup, penalty tracing from a violated section, deterministic full-text retrieval, and graph schema summaries, all running locally via Docker.

Enables AI agents to look up an individual federal case's or defendant's outcome by docket number plus district or circuit, and to answer aggregate caseload-statistics questions such as counts of filings and terminations broken down by nature of suit, offense code, disposition, fiscal year, or district/circuit. Data comes from the Federal Judicial Center's Integrated Database, covering civil, criminal, and appellate filings that opinion/docket readers have no aggregate data for.

Enables an AI agent to search German federal law and ask cited legal questions, returning ranked passages or citation-backed answers and explicit refusals when the available corpus does not support an answer.

Enables an assistant to search French co-ownership law (the 1965 statute and 1967 decree) for the articles that answer a question, returning references, excerpts, Légifrance links, and an explicit refusal when the texts don't cover it, and to read an article's full official text with its entry-into-force and consolidation dates.

Exposes two tools over streamable HTTP: write_receipt, which issues a signed, hash-chained receipt for each cleared agent read using a per-writer bearer token, and verify_receipt, a public endpoint that checks a receipt against the published JWKS keyring. This lets agents and auditors prove what an answer relied on without contacting the issuer.

MCP server providing deep knowledge of Brazilian eSocial S-1.3, including validation rules, XSD fields, and official documentation, enabling AI agents to answer questions about eSocial events and compliance.

OpenLawMCP is an open-source legal AI research tool built to make AI-assisted legal research more reliable. A major problem with using AI for legal research is that it can give confident answers without showing whether the answer is grounded in real legal sources. For legal work, that creates a credibility problem. Users need answers that can be checked against actual legal material.

Enables voice-first assistants to answer small-business compliance questions for Idaho and New Mexico LLCs, returning short spoken checklists, the next filing deadline, plain-language explanations of terms, and quick website accessibility checks. Every fee and rule is cited to a statute or official source, and unsupported states or unverified details are labeled unknown.

Enables MCP clients to compute Portuguese vehicle taxes (ISV and IUC) and to estimate used-car price ranges from structured inputs. Every tax answer returns legal sources, explicit assumptions and a not-tax-advice disclaimer, while price estimates are clearly labelled as synthetic-data demos.

An MCP server providing direct, citable access to Finnish legislation by retrieving statute text from Finlex open data, enabling AI assistants to answer legal queries with accurate citations.

Answer a few questions. Get clean, jurisdiction-aware privacy policies and terms of service.

Enables retrieval and comparison of automotive regulations and standards, plus question answering where every answer must carry standard number, clause number, and original excerpt, with unsupported conclusions flagged for review. Java backends and Feishu can call it directly over MCP.

A FastMCP server that enables searching Korean legal documents and retrieving relevant articles to answer legal questions using the Open Law API.

Exposes 20+ tools that let any MCP-compatible client answer patent-rule questions from MPEP/USC/CFR via hybrid vector, lexical, and reranked search, hunt prior art across 100M+ patents through Google BigQuery, run automated 35 USC 112 compliance and claim-definiteness checks, and generate patent-style diagrams. It also supports a guided idea-to-draft-application workflow covering claims, specification, and formatting review for US and European filing.

Exposes 20+ tools that let MCP-compatible clients answer patent-rule questions via hybrid RAG search over MPEP, USC, and CFR, hunt for prior art across 100M+ patents through Google BigQuery, run automated claim and application compliance checks, and generate patent-style diagrams with Graphviz.

Enables hybrid retrieval and reranking over public Brazilian legislation, returning answers with literal per-sentence citations verified by code through search, answer, health, and source-listing tools over stdio or HTTP.