LLM Mart Basic
@llm-mart · Joined Jun 2026
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Access DeFi data from DexPaprika: token prices, liquidity pools, OHLCV, transactions across 34+ blockchains and 30M+ pools. Free, no API key needed. Install MCP: add https://mcp.dexpaprika.com/sse as SSE server, or install plugin: /plugin marketplace add coinpaprika/claude-market
Automate Discord tasks via Rube MCP (Composio): messages, channels, roles, webhooks, reactions. Always search tools first for current schemas.
Delegate tasks to OpenAI Codex CLI and Google Antigravity CLI from Claude Code. Say 'check with codex' or 'ask gemini for a second opinion' and Claude runs the other agent, keeps a topic-aware session, and critiques the result.
文档文字识别。用户提供 PDF/扫描件/图片(合同、发票、书页、截图),需要提取文字、转成可编辑文本时使用。扫描件自动 OCR(macOS Vision,中英文)。Document OCR: extract editable text from PDFs, scans, and images (contracts, invoices, book pages, screenshots) via macOS Vision.
Automate DocuSign tasks via Rube MCP (Composio): templates, envelopes, signatures, document management. Always search tools first for current schemas.
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content,
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
Automate Dropbox file management, sharing, search, uploads, downloads, and folder operations via Rube MCP (Composio). Always search tools first for current schemas.
电商素材工坊(中英双语)。用户需要生成电商主图、详情图、场景图、产品图合成、品牌叠加时使用。自动识别品类→匹配风格→场景感知合成→统一文字→自动质检→多平台适配→标准化交付。E-commerce product image studio: category detection, style matching, scene-aware compositing, text overlay, quality check, multi-platform adaptation, batch delivery.
Design and generate .envelope.json AI agent team definitions — the open standard for multi-agent teams with hierarchy, access policies, human-in-the-loop gates, and cron schedules.
Automate Figma tasks via Rube MCP (Composio): files, components, design tokens, comments, exports. Always search tools first for current schemas.
Automate Freshdesk helpdesk operations including tickets, contacts, companies, notes, and replies via Rube MCP (Composio). Always search tools first for current schemas.
Automate Freshservice ITSM tasks via Rube MCP (Composio): create/update tickets, bulk operations, service requests, and outbound emails. Always search tools first for current schemas.
Open-source growth playbooks for AI products, B2B SaaS, and developer tools. Covers Product Hunt launch, GitHub star growth, KOL/UGC strategy, ASO, and community building. MIT licensed.
Automate GitHub repositories, issues, pull requests, branches, CI/CD, and permissions via Rube MCP (Composio). Manage code workflows, review PRs, search code, and handle deployments programmatically.
Automate GitLab project management, issues, merge requests, pipelines, branches, and user operations via Rube MCP (Composio). Always search tools first for current schemas.
Automate Gmail tasks via Rube MCP (Composio): send/reply, search, labels, drafts, attachments. Always search tools first for current schemas.
Automate Google Analytics tasks via Rube MCP (Composio): run reports, list accounts/properties, funnels, pivots, key events. Always search tools first for current schemas.
Automate Google Calendar events, scheduling, availability checks, and attendee management via Rube MCP (Composio). Create events, find free slots, manage attendees, and list calendars programmatically.
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/update
Update
CoalWash self-update — check for a newer version and offer to apply it, or set how updates are handled.
/create-skill
Create skill
Create an AI skill from any source (URL, repo, PDF, video, notebook, etc.)
/install-skill
Install skill
One-command skill creation and packaging for a target platform
/sync-config
Sync config
Sync a scraping config's URLs against the live documentation site
/mc-validate
Mc validate
Generate and run validation queries for the current change
/mc-validate
Mc validate
Generate and run validation queries for the current change
/setup-code-intelligence
setup-code-intelligence
Check code-intelligence prerequisites (ripgrep + a language server) and print install hints
/ci-mockup-figure
Ci mockup figure
Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion
/editable-figure
Editable figure
Design concise overview, mechanism, or workflow figures as editable PowerPoint objects
/implement-review
Implement review
Run the implement-review staged-change review loop
/my-router
My router
Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill
/prun
Prun
Run prun: parallel delegation fan-out on Agy workers (the session coordinates)
/readme-polish
Readme polish
Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim
/vet
Vet
Vet the staged change: run the implement-review review loop (short alias)
/ci-mockup-figure
Ci mockup figure
Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion
/editable-figure
Editable figure
Design concise overview, mechanism, or workflow figures as editable PowerPoint objects
/implement-review
Implement review
Run the implement-review staged-change review loop
/my-router
My router
Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill
/prun
Prun
Run prun: parallel delegation fan-out on Agy workers (the session coordinates)
/readme-polish
Readme polish
Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间,让人与智能体在此协作
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16 views 0 likesMy AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.
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15 views 0 likes观澜 / Guanlan:AI Agent 的中文互联网研究、阅读与信源路由工具。
13 views 0 likesMac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…
15 views 0 likesSemantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.
28 views 0 likes