MCP server for code structure analysis across 20+ languages. Tree-sitter powered. Works with Claude Code and Claude Desktop.

AI control layer for ETABS structural analysis — 806+ database tables, AISC 360-16, NTC-CDMX, UBIM export. By Hugo Velasco.

MCP server for PDF structure analysis - read, inspect, and validate PDF internals

Local-first, deterministic repository structure and data lineage analysis

An MCP server that provides code structure and semantic analysis capabilities through Abstract Syntax Trees (AST) and Abstract Semantic Graphs (ASG)

A comprehensive Model Context Protocol server for accessing Protein Data Bank (PDB) with 28 structural biology tools for protein structure analysis, validation, and comparison

MCP server for AI agents — structured code analysis that cuts token usage by 87%

Go MCP server for codebase analysis using tree-sitter, with AST inspection, symbol extraction, and structural search.

Charles Proxy MCP server with live capture, structured traffic analysis, and agent-friendly tool contracts

27 practical AI tools (MCP server + CLI) — structured frameworks, data processing, and real computation for writing, analysis, coding, and business tasks.

Pi coding agent native codebase awareness toolkit — 7 structural analysis tools. Also supports MCP (Cursor, Claude Desktop, Windsurf, etc.)

MCP server for React Native spatial integrity and layout audit. Provides Ground Truth for your component tree by detecting margin pollution, token deviations, bridge crossings, and render traps. 15 tools for structural analysis, layout auditing, performan

Structural framing analysis as an MCP server with deterministic detection. The caller's agent runs the judge, so Frame Check bears zero LLM cost per query.

A high-performance code intelligence graph for LLMs and AI agents. Sub-second structural queries, impact analysis, and cross-repo API contracts for autonomous coding workflows.

aptu-coder: MCP server for AST analysis, call graphs, and code structure (tree-sitter)

Local-only Go static analysis engine with a built-in MCP server. Gives AI coding agents deterministic structural awareness: call graphs, impact analysis, symbol search, and more.

Dependency/import mapper MCP tool. Scans directories for import statements across 11 languages and outputs structured JSON for blast radius analysis before refactoring.

Agentic MCP pipeline that transforms LinkedIn saved jobs into structured career intelligence. Deterministic EROI scoring engine with skill gap analysis, golden-rule weighting, and automated KB write-back. Fully customizable — plug in your own methodology.

Local-first repository analysis engine: code structure, dependency impact, and data lineage via CLI, Python API, and a read-only MCP server. Deterministic by default.

Developer-focused MCP server with 23 tools for Python code analysis, structural editing, JSON repair, imports, encoding, Markdown/PDF export, diffs, and regex testing

Reasoning depth enforcement for LLMs. Seven structured analysis tools and 18 mental-model templates for Claude Code, Claude Desktop, Codex, and any MCP client.

🕸️ 3- Distributed MCP-based platform for AI incident analysis, with structured communication and traceability to support AI governance, Responsible AI and ethics-by-design.

A comprehensive Model Context Protocol server for accessing SureChEMBL chemical patent database with tools for patent search, chemical discovery, and structure analysis

Local codebase intelligence for AI coding agents: structural repo map, change-safety gates, MCP security receipts, and tamper-evident ChangeEvidence packets. Local analysis, zero API keys, no source-code egress.

Frame Check MCP server: deterministic structural framing analysis for AI-generated documents, with default-on frame-divergence block per FRAME_DIVERGENCE_CONTRACT_v1 c1.0. MCP surface delegates V4.2 judgment to the caller's agent model; zero Frame Check LLM cost per query.

A comprehensive Model Context Protocol (MCP) server that provides access to the AlphaFold Protein Structure Database through a rich set of tools and resources for protein structure prediction analysis.

strategy-mcp is an open source MCP server that exposes professional-grade product strategy frameworks as structured tools. Any MCP-compatible AI assistant (Claude, Cursor, Cline) can install it and immediately get access to structured strategy analysis, RICE, JTBD, competitive positioning, assumption mapping, and more.

Agent-oriented crawler analysis MCP server for access diagnostics, page understanding, crawl planning, and structured data extraction.

MCP server for structured women’s decision intelligence, scenario analysis, and evidence-based choice support.

MCP server for recursive deep reasoning — structured what-if analysis trees for Claude Code

The canonical NIPO ODIN analysis engine: diagnostics, structural map, corpus audit and language reference, as a CLI and MCP server.

A Node.js + TypeScript pipeline that ingests YouTube videos and produces structured JSON analysis with stable, source-linked artifact names

LLM planning agent over a forecasting backtest — strict tools, structured output, measured eval with failure analysis

Charles Proxy MCP server for AI agents with live capture, structured traffic analysis, and agent-friendly tool contracts

MCP server wrapping the Artificial Analysis public API. Enables AI agents to query LLM and multimodal model benchmarks, pricing, speed data, and track model updates via structured diffs.

Read-only Entra ID org-structure and access analysis via the Azure CLI session, as an entra CLI and an MCP server.

MCP server for FireCrawl web scraping integration. Supports both cloud and self-hosted instances. Features include web scraping, batch processing, structured data extraction, and LLM-powered content analysis.

The testing framework CAD never had — automated validation, interference detection, and structural analysis for STEP assemblies. Like pytest for mechanical design.

A powerful Model Context Protocol (MCP) server that enables AI assistants to analyze and read GitHub repositories with ease. Perfect for code analysis, repository exploration, and understanding project structures.

**Morphogenetic Innovation MCP Server** applies mathematical biology to technology landscape analysis, giving AI agents a structured way to reason about how innovations evolve, compete, and disrupt.

MCP server for citation-finding research workflows: claim extraction, multi-source paper search (arXiv/Semantic Scholar/PubMed/OpenAlex), citation quality scoring, structured paper analysis.

A Model Context Protocol (MCP) server that enables secure interaction with IoTDB databases. This server allows AI assistants to list tables, read data, and execute SQL queries through a controlled interface, making database exploration and analysis safer and more structured.

The official CoDRAG plugin for Paperclip. Give every AI agent deep structural codebase knowledge, blast radius analysis, and semantic search via MCP.

Data Science platform for code structure analysis, trace event-action chains through graph queries; perform code diagnostics and more! Notebooks, Force-directed graph visuals; follow your agent as it updates your files.

Franchise due diligence research inside any MCP-compatible AI client — one tool call delivers franchisor health scores, complaint trajectories, market saturation analysis, corporate structure investigation, and investment verdicts drawn from 8 parallel data sources.

Ganjoor MCP Server connects AI assistants and agents to the Ganjoor Persian poetry platform through the MCP. It exposes poetry, literary analysis, historical figures, audio recitations, and related cultural information as structured tools that AI applications can discover and use.

Free, local SEO + GEO (AI-search-citation) analysis for AI assistants - audits GEO/AI-crawler access, Core Web Vitals, structured data, security headers, mobile, and images with no signup or API key.

A Model Context Protocol (MCP) server that enables secure interaction with MySQL databases. This server allows AI assistants to list tables, read data, and execute SQL queries through a controlled interface, making database exploration and analysis safer and more structured.

TypeScript Model Context Protocol (MCP) server for SEO Insights. Provides SEO tools for backlinks, keyword research, and traffic analysis. Includes CLI support and extensible structure for connecting AI systems (LLMs) to SEO APIs

Enable AI assistants to perform real-time web searches, extract data from web pages, map website structures, and crawl websites systematically. Enhance your AI's capabilities with powerful tools for intelligent data retrieval and analysis from the web. Seamlessly integrate advanced search and extraction features into your MCP client workflows.

Local-first, human-approves-everything grocery replenishment as a ResonantOS add-on: runway analysis, fail-closed dietary checks, and a next-cart draft that structurally cannot check out. No accounts, no cloud, no telemetry — nothing leaves your machine.

MCP-based autonomous pentesting framework — Claude, ChatGPT, or Ollama orchestrate 70+ Kali Linux tools (nmap, sqlmap, Metasploit & more) for recon, exploitation, and post-exploitation, Wireshark packet analysis, and headless Chromium evidence capture. Fully containerized, authorization-enforced, structured pentest reports out of the box.

Competitive digital intelligence for AI agents — this MCP server delivers a full-spectrum analysis of any competitor's digital presence by orchestrating 8 specialist data sources in parallel. It is built for strategy teams, product managers, and AI-powered research workflows that need structured, scored intelligence rather than raw scraped data.

A complete AI infrastructure for analytical modeling — not just a REST API wrapper. Provides any MCP-compatible AI assistant with access to **[RASON](https://www.solver.com/rason)** by [Frontline Systems](https://www.solver.com) for building, analyzing, and solving optimization, simulation, data science, and decision models. Includes a searchable library of nearly 200 example models, starter templates for every model type, structural model analysis, and guided workflows for solving and result interpretation. An AI assistant connected to this server can formulate a model from a business problem description, find relevant examples, explain model structure, submit it for solving, and present results in a goal-oriented way — closing the loop with suggested next steps and improvements. **Example interactions:** - "Find me a portfolio optimization example" - "Build a scheduling model for 8 employees with shift constraints, solve it, and show the schedule" - "This model is infeasible — run diagnostics and suggest which constraints to relax"

# Fashion E-Commerce Intelligence MCP Server Empower your AI agents, copilots, and assistants with vertical domain-specific fashion intelligence. Built by [alexgenovese.com](https://alexgenovese.com), this Model Context Protocol (MCP) server provides automated **SEO auditing, category trend research, DTC demand forecasting, CRM segment enrichment, and campaign creative generation**—designed natively for Cursor, Claude Desktop, Claude Code, and any MCP-compatible environment. --- ## ⚡ What It Does | Capability | Without this server | With Fashion MCP | |---|---|---| | **SEO Auditing** | Manual checklists, generic advice | Automated **0-100 score** across 5 dimensions with fashion-specific validation (fit, material, color, season, schema, OG, Twitter Cards). | | **Trend Research** | Generic search queries | Deep category-level trend intelligence (trending keywords, colors, silhouettes, price tiers, market fit, confidence). | | **Demand Forecasting** | Spreadsheets & gut feel | Explainable weighted-rule forecast model: `baseline × trend × media × retention × inventory × seasonality` with backtesting. | | **CRM Segment Enrichment** | Static email lists | Customer segments enriched with trending colors/silhouettes/keywords, audience clusters, and ready-to-send targeted messaging. | | **Campaign Creative** | Standard copywriters per channel | Platform-specific campaign themes, hooks, value propositions, and ready-to-use creative briefs grounded in real-time trend data. | --- ## 🔧 Exposed Tools - `product_seo_audit`: Audit any fashion product listing for SEO best practices, structured schema, meta tags, and fashion relevance (fit, size, material). - `fashion_trend_analysis`: Analyze fashion trend data mapped from search engine and social media queries. *(Receives search data input seamlessly, no API key required)*. - `fashion_category_demand_outlook`: Get a rapid, light demand pulse check for a specific product category in a target market and season. - `fashion_dtc_forecast_analysis`: Generate complete DTC demand forecasts with scenario planning (base/upside/downside) and stock-out/overstock risk analysis. - `fashion_customer_trend_enrichment`: Map trending keywords, colors, and silhouettes onto existing CRM customer segments for targeted email/SMS campaigns. - `fashion_campaign_theme_recommendation`: Recommend conversion-optimized ad campaign themes, hooks, and creative briefs for Meta, Google, TikTok, or Email. --- ## 🔐 Privacy & Technical Features - **No API Keys Required:** All analysis, SEO audits, demand forecasts, and CRM enrichment tools run locally with the data you supply. Upstream search data for `fashion_trend_analysis` uses your existing Tavily MCP server. - **Explainable Outputs:** Every tool returns explicit `assumptions[]`, `dataGaps[]`, and `confidence` scores, so your agent always understands the reasoning behind recommendations. - **Zero-Config Local Cache:** Uses a local SQLite persistence layer (`~/.fashion-mcp/store.db`) to cache snapshots, feature stores, and forecast actuals for backtesting. ## 💻 Local Installation To install this stdio-based server locally via Smithery: ```bash npx smithery install alexgenovese/ecommerce-fashion-market-analysis ```

SAP ABAP MCP is a local-first Model Context Protocol server that enables AI coding agents to develop, test, analyze, and operate SAP ABAP systems through the official ABAP Development Tools HTTP services. It supports repository search and source editing, structured DDIC workflows, enhancement inspection, paged package navigation, source-backed object creation, semantic services, activation, ABAP Unit and ATC, transports, abapGit, RAP generation, debugging, bounded class and executable-program profiling, runtime dumps, traces and feeds, cross-system comparison, dependency analysis, guarded refactoring, and an opt-in same-origin Screen/GUI Status bridge. Curated compact, development, and assurance presets reduce tool-schema token use without removing capabilities from the default surface. The default local stdio mode can be extended with governed self-hosted Streamable HTTP, API-key roles, OIDC/JWT authentication, request-scoped SAP bearer forwarding, per-session isolation, rate limits, structured audit logs, or a side-effect-free embeddable Node.js API. It also includes browser OAuth Authorization Code with PKCE, a read-only transport assurance CLI and GitHub Action, BTP service-key profile import, and live-SAP evidence tooling. SAP profiles and credentials remain on the user's computer, with passwords and OAuth credentials protected by macOS Keychain or Windows DPAPI. SAP-dependent capabilities are validated against the user's own SAP release, configuration, and authorizations.

# Metis FCA Handbook AI Harness — MCP Server An MCP (Model Context Protocol) server that integrates the Metis FCA Handbook AI Harness into Claude Desktop and other MCP-compatible agents. **Tool name:** `evaluate_fca_handbook_applicability` Use this tool to analyze FCA Handbook applicability for a product, service, or firm. Returns structured compliance reasoning with verbatim handbook citations. ## Why choose The Metis FCA Handbook AI Harness? - **Efficiency** Multiplies effectiveness of compliance advice. Saves £80+ in token fees per Harness run. - **Deals with "Hard Problem"**, in which LLMs' token incentives prioritise training data so results are unreliable. - **Verbatim citations** Quotes verbatim entries from the FCA Handbook. Other AI systems struggle to do this. - **Matches real-world need** You do not have to start off knowing which sections you are looking for. Carries out structured searches across all 10,000+ FCA Handbook entries. - **Secure Design** Harness compartmentalisation, one-shot structure, and statelessness fits natively with emerging AI agent security standards such as OWASP Top 10 for Agentic Applications 2026. - **AI Accessible** Integrates easily with AI workflows and agents. Your LLM can use it as a tool. ## Design Principles The Harness is built on proven principles: - **Stateless** — Each request is independent; no session coupling - **One-shot** — Complete analysis in a single call; no multi-turn state - **Clear contract** — Explicit input/output schemas for easy integration - **Hosted** — Single canonical source; no version drift or stale data ## Use Cases ### Compliance AI Platforms Embed FCA reasoning as a service within your compliance platform. Users ask natural-language questions; your platform calls the Harness and presents structured reasoning. ### AI Agent Workflows Agents building compliance workflows can include FCA Handbook reasoning as a composed tool—no external API calls, just MCP configuration. ### Compliance Review Automation Integrate into document review or due-diligence pipelines. Automatically screen new rules against FCA applicability. ## For Regulatory Screening FS firms screening MCP servers will find: - **Simple model:** Stateless, no hidden state, no background jobs - **Clear contract:** Explicit input schema, output schema, error modes - **Transparent updates:** Version pinning; no automatic upgrades - **Single point of failure:** If the Harness is down, it is obvious; no cascading config issues - **Audit-friendly:** All calls logged centrally, not distributed

MCP server for semantic code search and codebase analysis — AST parsing, Tree-sitter, embeddings and vector search for AI assistants and LLMs

Code structure for coding agents: classes, functions, callers and headings with line numbers, as an MCP server and the sct shell command. 20+ languages, tree-sitter, no index.

MCP server for Tekla Structural Designer