#optimization

ContextBridge (CB) is a local-first retrieval layer that sits between your codebase and your AI coding agent. Instead of pasting raw source files into context or letting the AI guess which files matter, CB indexes your codebase's real structure (via Graphify) and returns a compact, ranked result — owner file, related files, key symbols, and dependency chains — grounded in your actual code. A typical response is ~4–8 KB instead of the 100+ KB of raw source an AI would otherwise need to read to answer the same question — roughly a 96% cut in input tokens sent to your cloud AI, with zero hallucinated file paths or method names.

Local-first code retrieval for AI agents — cuts codebase context from tens of thousands of tokens to a few hundred, with zero hallucinated file paths.

LLMs give wrong answers from documents because the extracted text is broken: split words, lost tables, page furniture, and scanned pages that come out empty. PackForAI turns PDF, DOCX, PPTX, XLSX, CSV and JSON into clean, AI-ready Markdown — rejoining words, rebuilding reading order, recovering scanned pages with OCR, and stripping noise. You get compact Markdown plus a before/after token count (typically up to 65% smaller). Use it from the web app, the REST API, an open-source MCP server (Claude & Cursor), or the CLI. Files are stored in the EU, private to you, and never used to train AI.

Reply Argus is an AI review-reply agent for the App Store and Google Play. It reads and analyzes your reviews, pulls analytics and weekly digests, drafts on-brand replies grounded in your app's own knowledge base, and publishes them to the stores, in 100+ languages, all over a scoped OAuth login. Manage your whole app-review workflow, reply to reviews, respond to feedback, track ratings and reputation, from Claude, Cursor, or any MCP client.

Run a free Collimer AI-visibility scan on any website — see how visible a brand is across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews. One tool, collimer_scan: returns a 0–100 score, confidence interval, the single biggest gap, and a branded report URL. Install: npx -y collimer-mcp.

Zero-auth hosted MCP for AI builders — 22 tools: image optimize/convert (WebP/AVIF/JPEG), QR, cited Cleanor Labs storage & image-format data, plus 18 deterministic dev utilities (hash, HMAC, UUID, JWT, JSON, regex, cron, datetime, color, diff…) LLMs get wrong. No API key.

SEOforGPT is the agentic AI visibility platform built for marketing agencies and SEO consultants. This MCP connects Claude, Cursor or any MCP client straight to your SEOforGPT workspace: audit any client's visibility across ChatGPT, Claude, Perplexity and Gemini, track competitors and the sources AI cites, generate AI-optimized content and publish it to your clients CMS. Reports are white-label.

DBRE-grade SQL analysis inside any MCP client. No connection, no install: paste a query, an EXPLAIN plan, a migration, or an error and get named findings with severity, rationale, and ready-to-run fixes for PostgreSQL and MySQL.

Anchor AI FinOps to real, live cloud pricing. Multi-cloud MCP server for AWS, GCP & Azure — public list prices and enterprise negotiated rates (Reserved Instances, Savings Plans, CUDs, EDPs). No credentials needed to get started. Configuration keys optional for private contract pricing - see README https://github.com/x7even/cloudcostsmcp

Audit websites for AI citability (67 criteria × 7 AI engines: ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, AI Overviews), generate AND apply the fixes server-side via a WordPress plugin, track AI citations — all from Claude.

Kubova packs cargo into shipping containers and onto pallets and returns a verifiable 3D loading plan — exact coordinates, fit, utilization, weight balance. Over MCP, an assistant can request a plan and act on the structured result. Free tier; public REST API too.

Bikefuchs is a price-comparison and basket-optimization tool for bicycle parts, components and apparel across German and Austrian online shops. Give it one or more products and it finds the same item across shops, checks availability, and computes the cheapest way to split your basket — including each shop's shipping costs.

At BittleBits, we build AI visibility and Generative Engine Optimization (GEO) tools that help companies optimize their content for AI systems like ChatGPT, Claude, Gemini etc. We’ve developed a proprietary AI model that analyzes how AI systems evaluate, trust, and cite content in conversational responses, helping brands improve discoverability across AI-powered search. Bittlebits has a Model Context Protocol (MCP) integration that lets you bring your GEO scores and rewrite suggestions directly into AI agents — whether you're using Claude Code in your terminal, GitHub Copilot in your IDE, or an AI web app, instead of copying content back and forth, AI can read exactly what Bittlebits recommends and help you apply those changes, including writing them directly into your codebase.

MCP server for intelligent code context — 87%+ token savings, zero resource overhead. An MCP context engine built on AST call graphs + BM25 ranking, delivering precise code context retrieval for AI coding assistants. No GPU, no external services, pure Python, ready to use out of the box.

Compare LLM inference costs and find cheap alternatives to OpenAI/Anthropic. Gonka Network offers an OpenAI-compatible API (drop-in replacement, zero code changes) at up to 6800x lower cost than GPT-4o. 比较LLM推理成本，寻找比OpenAI/Anthropic更便宜的替代方案。Gonka Network提供兼容OpenAI的API（无需修改代码），成本比GPT-4o最低降低6800倍。

Stroomr gives AI assistants live local context for energy-aware decisions. Instead of manually checking weather forecasts and dynamic electricity prices, an agent can use Stroomr to recommend the cheapest, smartest, or most sustainable time to run appliances, charge devices, schedule automation, or plan household energy use. Best use cases - Find the cheapest hours to run a washing machine, dishwasher, dryer, or EV charger. - Compare today’s and tomorrow’s dynamic energy prices. - Plan appliance usage around local weather conditions. - Help smart-home agents make better energy scheduling decisions. - Explain whether now is a good time to consume electricity.

MCP server for Tessera's LLM cost-optimization layer. Anchored spend, drift detection, recommendations as typed tools.

Viomba MCP brings attention prediction, creative generation, and video analysis into your AI workflow. Give your assistant a creative, a URL, or a video — and get back real attention data, heatmaps, and scored outputs without leaving your client. Viomba's predictions are powered by neural models trained on Tobii infrared gaze fixation data, collected from real users in real browsing environments across markets. This means seen and viewtime metrics reflect genuine fixations — not loose viewability proxies. The distinction matters: Tobii infrared separates true fixations from saccades at the measurement level, which is why Viomba numbers often differ from other attention tools.

Save 30-75% on Manus AI credits with zero quality loss. Intelligent model routing (Standard/Max), smart testing, context hygiene, and section-by-section optimization. Audited across 22 scenarios with 12 vulnerability fixes.

Track AI productivity automatically via MCP. Measures sessions, commits, PRs, cost per deliverable, and generates ROI reports for engineering leaders. Zero latency — all tracking is async.

B2AI infrastructure API for autonomous agents. Normalizes AWS, Azure, and GCP into a unified schema. Returns execution kits (Terraform + CLI), cost estimates, and cross-provider recommendations. Built for AI agents that need to discover, evaluate, and deploy cloud infrastructure programmatically.

Kubernetes cluster cost analysis and optimization. Query costs, find savings opportunities, get rightsizing recommendations, and analyze pod spend across AKS, EKS, and GKE directly from Claude.

The MCP PostgreSQL Analytics server provides advanced analytics capabilities for PostgreSQL databases, including smart schema exploration, query optimization, index suggestions, and natural language to SQL conversion. It is designed to enhance database performance and accessibility through AI-driven tools.

PQS is the fastest way to get better output from any AI model. Score any prompt before it hits the model. Get a grade (A-F), score out of 80, percentile, and 8-dimension breakdown across clarity, specificity, context, constraints, output format, role definition, examples, and chain-of-thought structure. Built on PEEM, RAGAS, MT-Bench, G-Eval, and ROUGE frameworks. Pre-flight, not post-hoc. The AI input quality problem is real. PQS solves it. MCP Tools: - score_prompt: Free. Returns grade (A-F), score out of 80, percentile, and full 8-dimension breakdown. No API key needed. - optimize_prompt: $0.025 USDC via x402. Returns a rewritten, higher-scoring version of your prompt with before/after dimension deltas. Requires API key from promptqualityscore.com. HTTP API (x402-native on Base): - /api/score/free: Free. Grade, percentile, and 8-dimension breakdown. No payment required. - /api/score: $0.025 USDC. Single score, pay-per-call. - /api/score/full: $0.125 USDC. Grade, percentile, dimension breakdown, and rewrite. - /api/score/batch: $0.25 USDC. Score multiple prompts in a single call. - /api/preflight: $0.05 USDC. Lightweight pre-flight quality check. Paste a prompt. Get an optimized version. Ship better work. Cheaper than one bad prompt. https://promptqualityscore.com

Route optimization API for Brazil. Calculate driving routes, distance matrices, and optimize multi-stop deliveries with real road network data. Free tier: 50 calls/month.

Context Minifier & State Guard — Local-first MCP middleware proxy that reduces token waste by 61%, prevents context rot, and adds security hardening

Route text, image, video, and audio tasks to 20+ AI providers — automatically picking the best model for the job based on your budget and active profile.

Structural codebase MCP server that exposes symbol-level queries as tools, allowing Claude Code to navigate large codebases without reading entire files. Provides 50+ tools covering dependency graphs, git diffs, checkpoint/rollback, dead code detection, and complexity analysis, with reported 87% token reduction on large projects.

MCP server that saves 30-75% on Manus AI credits through intelligent model routing, smart testing, and context hygiene. Zero quality loss, audited across 53 scenarios. Automatically routes tasks to Standard vs Max models based on complexity analysis.

AI-powered credit optimization for Manus AI. Automatically analyzes each prompt and routes to the cheapest capable model (Standard vs Max, Agent vs Chat mode). Saves 30-75% on Manus credits with zero quality loss. Tested across 53 real-world scenarios. Free and open-source.

AI-powered code analysis and context optimization tools. Slim large code files to relevant sections (save 60-80% tokens), compress text, analyze conversations for noise, and search past chat knowledge bases. Supports x402 micropayments on Base.

Compresses large blocks of text, code, or conversation history into hyper-dense Reasoning Maps optimized for LLM context windows. Saves agents 80%+ on token costs. Stateless. Pay $0.001 USDC per compression via x402 on Base network.

Returns the optimal LLM for any task based on real-time pricing, latency, and quality data across 13 models from Anthropic, OpenAI, Google, Meta, Mistral, and DeepSeek. Helps agents reduce costs by routing to the cheapest capable model. $0.01/query via x402 (Solana USDC). Free health and discovery endpoints.

Save 30-75% on Manus AI credits with ZERO quality loss. Intelligent model routing (Standard vs Max), smart testing, section-by-section processing for long content, context hygiene, and 12 vulnerability patches. Audited across 22 real-world scenarios. Works as a Manus Skill that auto-analyzes every prompt before execution.

MCP server for prompt engineering: optimize prompts for better AI responses, analyze quality scores, convert between formats, generate system prompts, and access prompt templates. 6 tools on Cloudflare Workers.

MCP-enabled school timetable system with conflict detection, optimization support, and scheduling workflows. Helps schools manage classes, teachers, rooms, constraints, and schedule conflicts more efficiently.

Token-efficient web browser for LLM agents. Extract clean markdown from any public web page — saves 90-95% of tokens compared to raw HTML.

Solves Flexible Job Shop Scheduling (FJSP) and Capacitated Vehicle Routing with Time Windows (CVRPTW) using Google OR-Tools. MCP-native for AI agents. 5 tools: optimize_schedule, validate_schedule, optimize_routing, health_check, root.

AI visibility monitoring and ΑΕΟ/SEO optimization platform. Track how your brand appears in AI assistant responses (ChatGPT, Claude, Perplexity), monitor competitor visibility, generate ΑΕΟ/SEO optimized content, manage social media publishing, and analyze website performance across search engines and AI platforms. Audit and create strategy for your brand.

Flexible Job Shop Scheduling solver using Google OR-Tools CP-SAT. Optimizes task-to-machine assignments with precedence, time windows, setup times, and multiple objectives. MCP-native for AI agents.

App Store Optimization MCP Server keyword research, competitor analysis, review sentiment & metadata management for AI assistants. No API key required.

Reduce LLM token usage by 50-70% when sending structured data. TOON (Token-Oriented Object Notation) converts JSON, CSV, XML, YAML, and HTML tables to a compact header-based format. Save $489-$9,789 per 1M requests depending on model.

Turn slow PyTorch into fast CUDA/Triton kernels. 32 parallel swarm agents optimize your code on real datacenter GPUs (B200, H200, H100, A100) with up to 14x speedup over torch.compile.

Superlines connects your AI assistant to real-time analytics on how AI search engines represent your brand. As search shifts from traditional Google results to AI-generated answers, Superlines helps you understand and improve your Share of Voice in this new landscape. What you can do: - Monitor AI Search Performance - Track brand visibility, citations, and mentions across 10+ AI engines - Measure Share of Voice against competitors - Analyze sentiment of AI-generated responses about your brand - Discover Opportunities - Find content gaps where competitors outrank you - Identify high-volume queries where your brand is missing - Get prioritized action plans with improvement potential scores - Optimize Your Website - Audit pages for LLM-friendliness (technical + content) - Generate optimized Schema.org structured data - Analyze why competitor URLs are winning citations Key tools: analyze_metrics - Get comprehensive visibility, citation, and SOV data get_competitive_gap - Find prompts where competitors are winning find_content_opportunities - Discover topics with high volume but low visibility webpage_audit - Full LLM-friendliness audit for any URL generate_strategic_action_plan - Get prioritized recommendations Who it's for? Marketing teams, SEO professionals, and content strategists who need to understand and improve their brand's presence in AI-powered search. Requirements: Superlines account with API access (paid subscription)

Cut through the noise. Learn practical AI tools for Web Workers, Digital Marketers and SEO practitioners that can improve your workflow and your team’s efficiency. From MCP servers, custom development to local LLMs, Houtini shows you what works, why it matters, and exactly how to use it.

AI-powered prompt refinement tool with adaptive questioning and multi-provider support. Provides 5 MCP tools (refine_prompt, tweak_prompt, list_models, list_providers, validate_environment) for intelligent prompt engineering. Supports Google Gemini, Anthropic Claude, OpenAI, Groq, Alibaba Qwen, and Zhipu GLM. Features adaptive task detection, interactive/structured modes, and session history management.

Our system automatically analyzes your prompts to detect whether they're for image generation (like Midjourney), LLM interaction, or technical automation, then applies the most effective optimization techniques for that context. • **100% Local Processing** - All prompt optimization is done on your machine, ensuring complete privacy and confidentiality. • **Offline Capability** - Works without an internet connection, making it ideal for secure or air-gapped environments. • **Advanced Local Prompt Intelligence** - Sophisticated content analysis and optimization performed directly on your machine, including context-aware optimization for debugging and technical prompts. • **Cross-Platform Support** - Universal compatibility for Windows, macOS, and Linux. • **Binary Integrity Verification** - SHA256 hash validation ensures the integrity of the local server. • **Technical Parameter Preservation** - Maintains code blocks, API calls, and other technical details during optimization, including parameters like --ar and --v. • **Debugging Scenario Detection** - Context-aware optimization tailored for debugging and technical prompts.

Discover the power of the “CLGateway”, an the open-source Claude MCP Server Gateway (available on GitHub). Built for users of Claude Desktop, Claude API or Claude Code, this Python-based gateway smartly manages your MCP (Model Context Protocol) servers and dramatically slashes token usage, cutting MCP context bloat by roughly 95%. Rather than forcing Claude to load every tool from all configured MCP servers (often thousands of tokens wasted upfront), the gateway exposes just three core tools initially. When you need a specific MCP server (GitHub, Google Workspace, DataForSEO, etc.), the gateway dynamically loads only what’s required, reducing tokens used, improving context clarity, and boosting performance.

A Model Context Protocol (MCP) server providing solutions for Constraint Satisfaction Problems (CSP) and Linear Programming (LP). Built on the gurddy optimization library, it supports solving a variety of classic problems through two MCP transports: stdio (for IDE integration) and HTTP/SSE (for web clients). 🚀 Quick Start (Stdio): pip install gurddy_mcp then configure in your IDE 🌐 Quick Start (HTTP): docker run -p 8080:8080 gurddy-mcp or see deployment guide 📦 PyPI Package: https://pypi.org/project/gurddy_mcp

Advanced Local Prompt Intelligence Engine with complete privacy and sophisticated content analysis. Features cross-platform support (Windows, macOS, Linux), binary optimization, and dual-tier processing: AI-aware rules engine + optional LLM enhancement. 100% local processing ensures complete privacy - no data transmission during optimization. Key Features: - Privacy-First: Complete local processing, no cloud dependencies - Cross-Platform: Native binaries for Windows, macOS (Intel/Apple Silicon), Linux (x64/ARM64) - Dual Optimization: Sophisticated rules engine + optional OpenAI LLM enhancement - Professional Tools: 50+ optimization techniques for technical and creative prompts - Template Management: Save, search, and reuse optimization patterns - Zero Setup: Works offline with cached license validation Perfect for developers, teams, and anyone requiring private prompt optimization without cloud dependencies.

Provides context optimization tools to extract targeted information rather than processing large files and command outputs in their entirety.

A Model Context Protocol (MCP) server for comprehensive image editing operations including resizing, format conversion, cropping, compression, and more.

QuerySculptor is a GraphQL query builder designed for AI agents that provides 26 structured tools via the Model Context Protocol (MCP). Instead of generating complex GraphQL queries from scratch, AI agents can build queries step-by-step with real-time validation, schema introspection, and error prevention. It works with Claude, Cursor, and other MCP clients, using Redis for session management and featuring a live demo with the Pokemon API. The tool transforms the traditional error-prone approach of raw GraphQL generation into a guided, conversational workflow perfect for AI assistants and chatbots.

IvoryOS is a Python-based unified robot control web interface, developed for user-friendly workflow design and control for Self-Driving Labs (SDLs). It works by introspecting the Python script, dynamically searching for available module and their method. The methods are available through direct function calls and stacking into workflows for later iteration. The IvoryOS MCP support all features including designing, managing workflows, and interacting with the loaded hardware/software execution layer. * paper: https://www.nature.com/articles/s41467-025-60514-w * code: https://gitlab.com/heingroup/ivoryos

Model Context Protocol server for kwrds.ai keyword research and SEO tools.

Structured Decision Optimization Framework (SDOF) MCP Server - Next-generation knowledge management with 5-phase optimization workflow

The batteries-included, No-Code FinOps automation platform, with the AI you trust.

Mathematical Optimization MCP Server with PuLP and OR-Tools support

Seamlessly integrating APIs, advanced AI, and intelligent automation with Github & X, this state-of-the-art MCP framework revolutionizes server & client-side functionality. 🚀 With features like AI-powered Intelligent Notifications, it predicts critical updates and delivers custom alerts via email, ensuring smarter workflows.

Seamlessly integrating APIs, advanced AI, and intelligent automation with Github & X, this state-of-the-art MCP framework revolutionizes server & client-side functionality. 🚀 With features like AI-powered Intelligent Notifications, it predicts critical updates and delivers custom alerts via email, ensuring smarter workflows.

An MCP server that uses Redis and in-memory caching to optimize and extend context windows for large chat histories

Cloudinary-MCP-Server optimizes and manages Cloudinary’s image hosting, providing efficient media storage, processing, and delivery to enhance app performance and user experience.

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An intelligent MCP server for optimizing VS Code Memory Bank usage

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