Your AI development stack, curated

The best AI coding tools, MCP workflows, and Claude Code skills — organized for developers. From editor setup to production integrations.

Build your AI stack

Tools, MCP servers, and skills that work together — from editor to production.

AI Coding Tools
8+ tools indexed
Editor extensions, code completion, pair programming tools. Cursor, Windsurf, Copilot, and more.
MCP Servers
6+ MCP servers indexed
Connect your AI to GitHub, databases, browsers, search, and production infrastructure.
Claude Code Skills
6+ skills indexed
Reusable workflow modules for debugging, refactoring, code review, and planning.

MCP Servers

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Langfuse MCP Server

Langfuse documents two MCP surfaces: a hosted Prompt Management server at `https://cloud.langfuse.com/api/public/mcp` (streamable HTTP, built into the platform per langfuse.com/docs/prompt-management/features/mcp-server) with tools such as `createTextPrompt`, `createChatPrompt`, `getPrompt`, and `updatePromptLabels`; and a public Docs MCP at `https://langfuse.com/api/mcp` for semantic search over Langfuse documentation (`searchLangfuseDocs`) without authentication. The legacy `langfuse/mcp-server-langfuse` Node server remains for local command-based setups with LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY. Langfuse positions MCP for agentic onboarding—IDE agents can add tracing to OpenAI, Anthropic, or LangChain codebases from the Get Started agentic tab.

Anthropic Remote MCP Connector

Anthropic documents remote Model Context Protocol connectors in Claude Help Center and platform.claude.com docs: users add publicly reachable MCP server URLs so Claude clients (claude.ai, Claude Desktop, Cowork, mobile) connect from Anthropic cloud infrastructure rather than the local machine. Team and Enterprise admins add connectors in Admin settings; individuals enable them under Settings > Connectors. The Messages API MCP connector (beta header anthropic-beta: mcp-client-2025-11-20) accepts mcp_servers entries with type url, name, and https URL, paired with mcp_toolset tools entries; servers must support streamable HTTP/SSE and be internet-accessible to Anthropic IP ranges.

dbt MCP Server

dbt Labs documents an official Model Context Protocol server at docs.getdbt.com/docs/dbt-ai/about-mcp (repository dbt-labs/dbt-mcp) that exposes governed access to dbt project metadata, lineage, CLI actions, and dbt Platform APIs for Claude, Cursor, and custom MCP clients. Local mode runs via `uvx dbt-mcp` with environment variables such as DBT_PROJECT_DIR, DBT_HOST, DBT_TOKEN, DBT_PROD_ENV_ID, and DBT_USER_ID; remote mode connects over HTTP/SSE to a managed dbt Platform MCP endpoint with OAuth. Documented tool groups include product-doc search (`search_product_docs`, `get_product_doc_pages`) and server metadata helpers, with additional development and deployment tools synced from the GitHub README per release.

Milvus MCP Server

The zilliztech/mcp-server-milvus project (documented at milvus.io/docs/milvus_and_mcp.md) exposes Milvus vector-database operations to MCP clients such as Claude Desktop and Cursor. The recommended launch path is `uv run src/mcp_server_milvus/server.py --milvus-uri http://localhost:19530` without a separate install step, with optional `MILVUS_URI`, `MILVUS_TOKEN`, and `MILVUS_DB` environment variables. Tools listed in Milvus docs include `milvus-text-search`, `milvus-hybrid-search`, `milvus-multi-vector-search`, `milvus-query`, and `milvus-count` for collection management, semantic retrieval, filtered hybrid search, and entity counts.

Mem0 MCP Server

Mem0 documents a hosted Model Context Protocol server at https://mcp.mem0.ai/mcp that exposes Platform memory tools (`add_memory`, `search_memories`, `get_memories`, `update_memory`, `delete_memory`, `delete_all_memories`, `delete_entities`, `list_entities`, `list_events`, `get_event_status`) to Claude, Claude Code, Codex, Cursor, Windsurf, VS Code, and OpenCode. Setup uses `npx mcp-add` with HTTP transport or manual JSON/TOML client configs; Codex requires `MEM0_API_KEY` as bearer token per docs.mem0.ai/platform/mem0-mcp. The cloud server needs a Mem0 Platform API key from the dashboard and Node.js for the installer—no local vector database required for the hosted path.

ClickHouse MCP Server

The open-source ClickHouse MCP server (PyPI package `mcp-clickhouse`, repository ClickHouse/mcp-clickhouse) exposes MCP tools such as `run_query`, `list_databases`, and paginated `list_tables` against ClickHouse clusters, defaulting to read-only SQL unless `CLICKHOUSE_ALLOW_WRITE_ACCESS` is enabled. Optional chDB extras add `run_chdb_select_query` for embedded queries over files and URLs. HTTP/SSE transports require authentication via `CLICKHOUSE_MCP_AUTH_TOKEN`, FastMCP OAuth/OIDC providers, or explicit `CLICKHOUSE_MCP_AUTH_DISABLED=true` for local dev; a `/health` endpoint supports orchestrator probes without credentials per README guidance.

Claude Code Skills

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AI subscription monetization claims due diligence

Converts consumer-AI subscription announcements into a planning checklist for product, finance, and partnerships teams. The workflow separates test-market scope (countries, price tiers, free-tier continuity) from analyst revenue extrapolations and capex guidance cited in the same news cycle. It references CNBC reporting on May 30, 2026 that Meta will test Meta AI subscriptions at $7.99 and $19.99 per month starting next month in Singapore, Guatemala, and Bolivia while keeping a free tier; that nearly 98% of Meta's $56.3 billion Q1 revenue still came from ads; Zuckerberg said a cloud business is "definitely on the table"; Meta raised 2026 AI capex guidance to $125–$145 billion; and Wolfe Research analysts estimated subscriptions could reach about $3 billion in 2027 revenue growing to $16 billion by 2030—without treating media projections as internal forecasts.

Private AI funding and valuation claims due diligence

Structures verification of headline private-market AI funding rounds into an evidence checklist for strategy, finance, and partnerships teams. The workflow separates announced valuation, round size, lead investors, previously committed capital, and revenue run-rate figures from independently confirmable filings or issuer press releases. It cites CNBC reporting on May 28, 2026 that Anthropic announced a $65 billion Series H at a $965 billion valuation led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital—including $15 billion of previously committed investments with $5 billion from Amazon—surpassing OpenAI's reported $852 billion valuation after its March funding round, while Anthropic cited a $47 billion revenue run rate and releases of Claude Opus 4.8 and Claude Mythos Preview—without treating media valuations as internal planning numbers.

Hyperscaler cloud commitment due diligence review

Turns announcements of multi-year cloud spend commitments and earnings-day infrastructure deals into a finance-and-platform checklist. Teams separate headline dollar totals (for example five-year AWS purchase obligations) from average annual run rates, prior amended agreements, and what is actually earmarked for AI GPUs versus general-purpose silicon. The workflow maps public claims to internal FinOps data before revising data-platform budgets or agentic-AI roadmaps. It cites CNBC reporting on May 27, 2026 that Amazon disclosed a $6 billion five-year Snowflake commitment covering Graviton and AI GPUs alongside Snowflake's fiscal Q1 beat ($1.39 billion revenue, 39-cent adjusted EPS vs analyst expectations) and an undisclosed Natoma acquisition—without treating media figures as procurement instructions.

AI memory and HBM supply-chain claims due diligence

Structures verification of public claims about AI-driven memory shortages, high-bandwidth memory (HBM) demand, and trillion-dollar memory-chip valuations into an evidence checklist for finance, procurement, and platform teams. The workflow separates analyst price-target moves, year-to-date equity rallies, and vendor statements about agentic-AI workloads from independently observable supply signals (long-term agreements, stated capacity constraints, peer pricing power). It cites CNBC reporting that Micron crossed a $1 trillion market cap on May 26, 2026 after UBS raised its price target from $535 to $1,625, and that SK Hynix joined the trillion-dollar club on May 27, 2026 with shares up roughly 250% year to date amid AI chip demand lifting South Korea's Kospi—without endorsing any single stock call.

Advanced chip roadmap claims due diligence review

Turns public semiconductor announcements into a verification checklist when vendors claim novel scaling laws, stacked logic architectures, or nanometer-class equivalence without independent benchmarks. Teams separate marketing nomenclature from manufacturing readiness by demanding yield, thermal, packaging, and third-party validation evidence—patterns highlighted when CNBC reported Huawei's LogicFolding and τ Scaling Law claims alongside analyst skepticism about true 1.4nm-class process breakthroughs without EUV access. The skill also maps export-control context (ASML EUV restrictions) and competitive implications for GPU vendors operating in constrained geographies.

AI economic benefit distribution readiness review

Converts public-policy and labor-relations guidance around AI-driven wealth into a planning checklist for organizations operating in semiconductor-heavy economies. Teams document how AI productivity gains translate—or fail to translate—into worker bonuses, public dividends, or reinvestment; assess concentration risk when chipmakers dominate equity indices; and prepare dialogue frameworks for recurring labor-management disputes as agentic automation scales. The skill cites CNBC reporting on South Korea's deputy prime minister urging that AI benefits reach the public amid Samsung strike negotiations, Kospi gains led by Samsung and SK Hynix, and debates over distributing AI-sector tax windfalls—without prescribing specific tax policies beyond verifying stakeholder messaging against cited facts.

AI News

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