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"Using a second LLM to collaborate with a primary LLM for problem-solving and quality improvement" matching MCP servers:

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    An MCP server that provides 46 tools for construction quality management, enabling users to generate and review documents like ITP, NCR, and test reports using a domain ontology and legal standards.
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    MIT
  • F
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    AgentBureau provides the legal and physical infrastructure for AI agents to operate within the German jurisdiction. We bridge the gap between digital intelligence and real-world action by providing "Embodiment-as-a-Service." Through our API, agents can perform legally binding actions—like sending faxes, mailing physical letters, issuing invoices, forming entire companies (GmbH/UG), ...
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  • A
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    Turn Claude into an ISO 27001 compliance assistant - controls, risk register, policies, evidence tracking, SoA generation, and full audit workflows in one local encrypted MCP server.
    96
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    MIT
  • A
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    Deterministic US equity-compensation tax optimizer. Six tools cover ISO/AMT exercise scheduling, NSO sell-vs-hold, RSU vest-and-sell, single-stock concentration, protective put / zero-cost collar pricing, and Section 1202 QSBS qualification. Federal plus 50-state plus DC tax math.
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    MIT
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    Provides comprehensive GDPR compliance assessment tools for AI/ML systems, including lawful basis determination, DPIA generation, and data subject rights handling. It also crosswalks GDPR requirements to EU AI Act obligations with AI-specific considerations throughout.
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    MIT
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    Exposes a check_ad_copy tool over stdio for LLM assistants to lint Korean cosmetics and health-food marketing copy for prohibited claims.
    42
    MIT
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    Torify gives AI agents the Japanese locale primitives that standard libraries lack — imperial era date conversion (wareki), qualified invoice number validation with NTA registry lookup, corporate number lookup (法人番号), postal code resolution, name romanization (Hepburn), and kanji-to-kana conversion via Yahoo! JLP. 31 endpoints total. No authentication required for MCP. Pay-per-call $0.02/call via
    MIT
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    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.
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    Apache 2.0
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    Turn Claude into an ISO 27001 compliance assistant — controls, risk register, policies, evidence tracking, SoA generation, and full audit workflows in one local encrypted MCP server.
    96
    MIT
  • F
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    Deterministic legal citation verification for AI-generated legal briefs. Three-layer verification: CourtListener database lookup, quote-match against primary source, and LLM edge-case verification. Free tier available.
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    Checks documents against international standards (e.g., ICAO, Hague-Visby) to verify internal consistency and completeness, returning a machine-readable verdict for agent decision-making.
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    MIT
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    MCP server for the Entyrix European business-registry (KYB) API, exposing 10 stdio tools for searching, looking up, and analyzing companies across multiple jurisdictions. Enables LLM clients to perform company registry searches, financial lookups, compliance checks, and more.
    10
    MIT
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    Trust and quality infrastructure for AI agents. 233+ quality-scored capabilities for company data, compliance checks, financial validation, and more. Every capability has a transparent SQS quality score. Audit trails on every call. EU AI Act support.
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    MIT
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    MCP server for validating and generating Brazilian documents (CPF, CNPJ, and bank boletos) with 6 tools, a resource, and a prompt.
    6
    MIT
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    Privacy-preserving AI gateway. Sanitises PII before prompts reach Anthropic / OpenAI / your LLM, then emits a signed cryptographic certificate per call (Ed25519 + RFC 3161 + Sigstore Rekor). EU GDPR + AI Act ready. Free tier 500/mo with BYOK.
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    MIT
  • F
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    Enables LLM agents to extract, validate, and mask personally identifiable information using deterministic regular expressions, reducing token usage and hallucination risks.
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