Cortex by AstroQuest — the code-context engine for AI agents. find, card, read, impact: understand a codebase in a few calls and ~10x fewer tokens. CLI + MCP server, local, Rust.

Ultra-fast indexed code search engine — faster than ripgrep on repeated searches, lighter than zoekt. Built-in MCP server for AI agents. Also does fast file finding (fd/find alternative).

Local code intelligence engine for AI coding agents. Answers "what breaks if I change this" and finds the right file for 99.4% fewer tokens than grep and read. Fully local, no GPU, no upload.

A desktop search engine for everything you write, read, and keep. Connect your Obsidian vault, projects, Calibre library, and code repos, then find anything with local hybrid search and expose through MCP.

Open-source, index-free web search engine for AI agents and people. No crawler, no search API bill, no piggybacking on other engines. MCP server for Claude Code, Codex, Cursor and Gemini CLI. Self-hosted.

Fast, agnostic indexed file & code search engine in Rust: CLI, daemon, MCP server, agent skill, library

A local model engine with a search engine and web crawler built in. Run your coding agents on your own GPUs, and get cited answers from your files, code, and the sites you crawl. One executable.

Open-source, self-hosted MCP server for project intelligence, semantic search, context engineering, and persistent agent memory for AI coding agents.

On-Page.ai SEO MCP server for search engine optimization work with Codex and Claude Code. Public docs, examples, and directory metadata for the hosted server.

A structural code search engine for Al agents.

Local-first context engine for AI-assisted coding. One SQLite index powering MCP-native search, symbols, references, and a knowledge graph... for any AI agent.

Ultra-fast cross-platform parallel code & symbol search engine in pure C (AVX2 & ARM NEON SIMD) with built-in MCP 2.0 server, code outlines, and ripgrep/fd compatibility for AI coding agents.

Reduce Claude Code token usage 54–67%. MCP server for web engineers — AI agents find symbols, trace callers, and map hierarchies by name instead of reading files. Built for TypeScript. Works with Claude Code, Cursor, and Codex.

A semantic search engine for files and code.

Local-first code search engine with a web UI, MCP server, and JSON API — lexical (Zoekt), symbol (ctags), and structural (ast-grep) search across your GitHub, GitLab, and local repositories. Single self-contained binary.

A semantic search engine for files and code.

The open-source web-browsing backend for AI agents & workflow engines. Ships a 42-tool MCP server for Claude Code/Cursor/Codex, a full REST API for n8n/Zapier/Make, federated multi-engine search, anti-bot stealth, and enterprise infrastructure (Postgres, Redis, BullMQ, MinIO). Self-host for $5/mo flat

Local code search engine for AI agents: incremental indexer, hybrid retrieval (BM25 + dense embeddings in Qdrant, RSF, per-language reranker) and an MCP server. Tree-sitter chunking, git branch/tag overlays. Java, Kotlin, Groovy, C#, Go, PHP, Python, JS/TS, C/C++, Delphi/Pascal, SQL and more.

AI search engine and MCP server for bots and agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search without grep, agent memory and RAG. Elasticsearch-compatible API; Corpus Hub serves hundreds of reference memory corpora.

TFModSearch — MCP server for AI agents (Claude Code, Codex, Claude Desktop) to search Terraform AWS modules with hybrid search engine combining semantic similarity (sentence-transformers), BM25 text relevance, and keyword matching. FastMCP-based, CPU-only inference.

Local code intelligence engine — three-tier FAISS + SQLite index with 10 MCP tools for semantic code search, blast radius analysis, and architectural investigation

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.

Lightweight code indexing and semantic search engine that helps AI agents write code faster while using fewer tokens. Parses codebases with Tree-sitter AST to generate structured headers, with optional LLM insights and vector embeddings. Integrates via MCP server or CLI. Supports TypeScript, JavaScript, C#

codegraph is a local-first code context engine and MCP server for repositories. It incrementally indexes source code into a lightweight SQLite graph, then exposes high-signal tools for symbol lookup, call graph traversal, impact analysis, related test discovery, and semantic search. Built in Go with a single-binary workflow, it is designed to work

Local RAG search engine and MCP server for AI agents (Claude Code, Cursor, VS Code): hybrid BM25 + semantic search with reranking over Markdown and Obsidian notes, PDF, Office files and emails, fast at tens of millions of passages. Backlinks, metadata filters, browser UI. Runs on your own GPU or CPU: no cloud, no API keys.

Offline semantic search for everything on your disk - documents, code, PDFs, scanned images (OCR), video by the second. 100% local AI: hybrid RAG with keyword + vector + rerank, no API key, no cloud. Desktop app + 26 MCP tools for Claude Code, plus a multi-engine web researcher that quotes sources verbatim. 本地离线多模态语义检索

Local-first AI agent memory and context engine for Claude Code, Codex, Gemini and MCP: cited Markdown recall, code search, hooks and cross-machine serving. · Wiki: https://forge.corbet.ch/corbet-fsl/cfetch/wiki

Local RAG search engine and MCP server for AI agents (Claude Code, Cursor, VS Code): hybrid BM25 + semantic search with reranking over Markdown and Obsidian notes, PDF, Office files and emails, fast at tens of millions of passages. Backlinks, metadata filters, browser UI. Runs on your own GPU or CPU: no cloud, no API keys.

Agent Fusion is a local RAG semantic search engine that gives AI agents instant access to your code, documentation (Markdown, Word, PDF). Query your codebase from code agents without hallucinations. Runs 100% locally, includes a lightweight embedding model, and optional multi-agent task orchestration. Deploy with a single JAR

MCP server that searches the Roblox DevForum and official creator docs so AI coding agents can debug Roblox games against real community and engine knowledge.

Graph-Augmented Code Intelligence RAG engine pairing deterministic AST call graphs with dense vector search to boost direct-callee Recall@8 from 0.0% to 53.3% (+53.3 pp) under a 5.8ms p95 latency bound. Powered by a QLoRA fine-tuned Qwen2.5 adapter (70.02 CodeBLEU), quality verification harness, and production Model Context Protocol (MCP) server.

Post-publish SEO performance MCP. Unifies **Google Search Console, Matomo, GA4, Microsoft Clarity, and AI-citation signals** per URL and emits a **verdict per post** (refresh / expand / merge / kill / double_down / hold) with deterministic reason codes and a 0-1 confidence score. Reporting only — never mutates posts. Works with any CMS via XML sitemap; optional Ghost Admin API integration for richer metadata. ## Tools - **posts.list** — discover posts via XML sitemap, JSON override, Ghost Admin API, or explicit URL list. - **posts.snapshot** — unified 30/60/90-day signal pull across every configured source for one URL. - **posts.decay_curve** — weekly GSC bucket + decay / plateau / growth classification. - **posts.verdict** — rule-based verdict engine: refresh, expand, merge, kill, double_down, hold. - **posts.refresh_brief** — markdown brief: verdict + reasons + numbers + suggested actions. - **posts.cite_loss** — list of LLMs that previously cited this URL but no longer do. - **cohort.report** — verdict engine across a cohort, ranked by verdict priority + confidence. - **gsc.quick_wins** — pages at positions 5-15 with low CTR, ranked by impressions. ## Prompts - **audit_cohort** — run cohort.report and generate refresh briefs for every actionable URL. - **find_quick_wins** — propose query-verbatim title and H1 rewrites for SERP underperformers. - **citation_loss_sweep** — find URLs that lost LLM citations and recover them. ## How it works Each source is best-effort: if its env vars are missing the field is omitted. Returns whatever is available. Optional DuckDB cache layer for historical comparisons. Platform-agnostic — works with WordPress, Hugo, Astro, Next.js, Webflow, Framer, Wix, Squarespace, Substack, Ghost, and any CMS that exposes a sitemap.

# 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 ```

MCP server for AI agents: find + grep in one query, with boolean logic, line-level conditions and compact, token-efficient output. Rust, stdio, cross-platform.

Grep finds strings. duckgrep answers questions.

Code intelligence for agents: find the code that matters and keep your context window and tokens lean.

Better code starts with the right context. OpenContextually finds, ranks, and explains what your coding agent should read first.

A precise local codebase map for AI coding agents: find, trace, and predict with file-line evidence.

The ripgrep of AI context: a zero-dependency C++23 CLI + MCP server for coding agents. Cut agent token costs by finding code without reading the repo, then keep large codebases off the complexity wall: blast radius, tests to run, quality deltas as you write. Every guess labelled, every loss published. Paddle out with a map.

Sub-millisecond AST structural & lexical BM25 code intelligence for AI coding agents. Ask your codebase a question, get exact file + symbol + line span in milliseconds.

Agentic code discovery: ask your codebase a question, get exact file + symbol + line span in milliseconds. No re-reading, no guessing, no index to build.

Find agent skills by meaning, not keywords. Local semantic search over shared SKILL.md repos for Claude Code, Codex and OpenCode, as an MCP server. Add any number of skills without growing your agent's context: nothing loads until you pick it.

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Cursor, Codex, Copilot, Gemini CLI. Local MCP server, free, open source.

Deterministic code-graph context engine for AI coding agents - PostgreSQL, Apache AGE and pgvector, over MCP and REST

Deterministic code-graph context engine for AI coding agents - PostgreSQL + Apache AGE + pgvector, MCP & REST, no LLM in the loop.

Drop-in token saver for Claude Code & MCP agents — auto-rewrite hooks + 10-tool MCP server + BM25/PageRank repo maps + call graphs in 7 languages + local RAG. Single Rust binary, 100% local, zero APIs.

Offline token-budget linter for agent context files — measures CLAUDE.md/AGENTS.md, finds dead references, returns a ranked plan.

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP server, free, open source.

zaungast is a read-only, offline MCP server for Teams: search chats, read conversations, surface trending topics, find people, and browse meetings & calls from the local on-disk cache — no Graph API, no cloud, no credentials — token-economical output for coding agents.

Index Salesforce org metadata into SQLite and serve it to Claude Code via MCP. 12 typed parsers, 18,600+ dependency relationships, full-text search. One tool call replaces dozens of file searches.

High-throughput agent context router and deterministic static analysis engine.

Xanther Context Engine MCP Server — Give your coding agent deep codebase understanding

SEO, AEO and GEO audit MCP server for Claude Code, Cursor and Codex. Audit a page as AI search crawlers see it, get a fix pack, apply and verify. Free, no API key.

Agentic detection-engineering workbench that runs Hayabusa against Windows EVTX logs, maps findings to MITRE ATT&CK, and surfaces detection coverage gaps, with an LLM orchestrating the tooling while detection logic stays human-owned.

Four free MCP tools to check whether AI engines can find, read and recognise a website. No account, no API key, no LLM calls.

Task-adaptive repository context engine for coding agents: local MCP, exact token budgets, and dependency-aware retrieval.

Local code-context engine + MCP server that feeds LLMs exact spans instead of whole files

Local codebase search MCP server for Claude Code, VS Code, Cursor, and AI agents.

Don't reverse engineer it twice. 17,000+ open-source tools built by reverse engineering closed apps, APIs, devices, protocols, file formats, games and AI tools. Search site + agent skill + MCP server, refreshed nightly.

Stop making AI agents uselessly rediscover your codebase.