CCM
/MCP
SkillsMCPMarketplacesDigestToolsAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Claude Code Marketplaces

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Skill index
  • MCP index
  • Marketplace index
  • Plugins Reference

Community

  • About
  • Tools
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by mertbuilds.com

Independent project, not affiliated with Anthropic
ariekogan avatar

Ateam Mcp

ariekogan/ateam-mcp
12 toolsSTDIO, HTTPregistry active
Summary

Bridges Claude, ChatGPT, Cursor, and other AI assistants directly to the ADAS multi-agent platform. Exposes twelve tools that let your AI read the ADAS spec, validate skill and solution definitions through a five-stage pipeline, deploy to production, and monitor health. The workflow is conversational: describe a customer support system with escalation, and the assistant builds the skill definitions, validates them, deploys, and confirms everything is running. No manual JSON authoring or dashboard hopping. Works over stdio for local setups or streamable HTTP at mcp.ateam-ai.com for remote access. Particularly useful if you're building production agent systems on ADAS and want to stay in your editor or chat interface instead of context switching to docs and deployment tools.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
inference shell
inference shell
create and run specialised agents in minutes
build now →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
inference shell
inference shell
create and run specialised agents in minutes
build now →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →

Tools

Public tool metadata for what this MCP can expose to an agent.

12 tools
adas_get_specGet the ADAS specification — schemas, validation rules, system tools, agent guides, and templates. Use this to understand how to build skills and solutions.1 params

Get the ADAS specification — schemas, validation rules, system tools, agent guides, and templates. Use this to understand how to build skills and solutions.

Parameters* required
topicstring
What to fetch: 'overview' = API overview + endpoints, 'skill' = full skill spec, 'solution' = full solution spec, 'enums' = all enum valuesone of overview · skill · solution · enums
adas_get_examplesGet complete working examples that pass validation. Study these before building your own.1 params

Get complete working examples that pass validation. Study these before building your own.

Parameters* required
typestring
Example type: 'skill' = Order Support Agent, 'connector' = stdio MCP connector, 'connector-ui' = UI-capable connector, 'solution' = full 3-skill e-commerce solution, 'index' = list all available ex...one of skill · connector · connector-ui · solution · index
adas_validate_skillValidate a skill definition through the 5-stage ADAS validation pipeline. Returns errors and suggestions to fix.1 params

Validate a skill definition through the 5-stage ADAS validation pipeline. Returns errors and suggestions to fix.

Parameters* required
skillobject
The full skill definition object to validate
adas_validate_solutionValidate a solution definition — cross-skill contracts, grant economy, handoffs, and LLM quality scoring.2 params

Validate a solution definition — cross-skill contracts, grant economy, handoffs, and LLM quality scoring.

Parameters* required
skillsarray
Array of skill definitions included in the solution
solutionobject
The full solution definition object to validate
adas_deploy_solutionDeploy a complete solution to ADAS Core — identity, connectors, skills. The Skill Builder auto-generates MCP servers from tool definitions. This is the main deployment action.4 params

Deploy a complete solution to ADAS Core — identity, connectors, skills. The Skill Builder auto-generates MCP servers from tool definitions. This is the main deployment action.

Parameters* required
connectorsarray
Array of connector metadata (id, name, transport, command, args)
mcp_storeobject
Optional: connector source code files. Key = connector id, value = array of {path, content}
skillsarray
Array of full skill definitions
solutionobject
Solution architecture — identity, grants, handoffs, routing
adas_deploy_skillDeploy a single skill into an existing solution.2 params

Deploy a single skill into an existing solution.

Parameters* required
skillobject
Full skill definition
solution_idstring
The existing solution ID to add the skill to
adas_deploy_connectorDeploy a connector — registers in the Skill Builder catalog and connects in ADAS Core.1 params

Deploy a connector — registers in the Skill Builder catalog and connects in ADAS Core.

Parameters* required
connectorobject
Connector metadata (id, name, transport, command, args)
adas_list_solutionsList all solutions deployed in the Skill Builder.

List all solutions deployed in the Skill Builder.

No parameter schema in public metadata yet.

adas_get_solutionRead solution state — definition, skills, health, status, or export. Use this to inspect deployed solutions.3 params

Read solution state — definition, skills, health, status, or export. Use this to inspect deployed solutions.

Parameters* required
skill_idstring
Optional: read a specific skill by ID (original or internal)
solution_idstring
The solution ID
viewstring
What to read: 'definition' = full solution def, 'skills' = list skills, 'health' = live health check, 'status' = deploy status, 'export' = exportable bundle, 'validate' = re-validate from stored st...one of definition · skills · health · status · export · validate
adas_updateUpdate a deployed solution or skill incrementally using PATCH. Supports dot notation for scalar fields and _push/_delete/_update for arrays.4 params

Update a deployed solution or skill incrementally using PATCH. Supports dot notation for scalar fields and _push/_delete/_update for arrays.

Parameters* required
skill_idstring
Required when target is 'skill'
solution_idstring
The solution ID
targetstring
What to update: 'solution' or 'skill'one of solution · skill
updatesobject
The update payload — use dot notation for scalars (e.g. 'problem.statement'), and tools_push/tools_delete/tools_update for array operations
adas_redeployRe-deploy after making updates. Regenerates MCP servers and pushes to ADAS Core.2 params

Re-deploy after making updates. Regenerates MCP servers and pushes to ADAS Core.

Parameters* required
skill_idstring
Optional: redeploy a single skill. Omit to redeploy all skills.
solution_idstring
The solution ID
adas_solution_chatSend a message to the Solution Bot — an AI assistant that understands your deployed solution and can help with modifications.2 params

Send a message to the Solution Bot — an AI assistant that understands your deployed solution and can help with modifications.

Parameters* required
messagestring
Your message to the Solution Bot
solution_idstring
The solution ID

ateam-mcp

Give any AI the ability to build, validate, and deploy production multi-agent systems.

This is an MCP server that connects AI assistants — ChatGPT, Claude, Gemini, Copilot, Cursor, Windsurf, and any MCP-compatible environment — directly to the ADAS platform.

An AI developer says "Build me a customer support system with order tracking and escalation" — and their AI assistant handles the entire lifecycle: reads the spec, builds skill definitions, validates them, deploys to production, and verifies health. No manual JSON authoring, no docs reading, no copy-paste workflows.

Why this matters

Today, building multi-agent systems requires deep platform knowledge, manual configuration, and switching between docs, editors, and dashboards. ateam-mcp eliminates all of that by making the ADAS platform a native capability of the AI tools developers already use.

The AI assistant becomes the developer interface:

Developer: "Create an identity verification agent that checks documents,
            validates faces, and escalates fraud cases"

AI Assistant:
  → reads ADAS spec (adas_get_spec)
  → studies working examples (adas_get_examples)
  → builds skill + solution definitions
  → validates iteratively (adas_validate_skill, adas_validate_solution)
  → deploys to production (adas_deploy_solution)
  → verifies everything is running (adas_get_solution → health)

Developer: "Add a new skill that handles address verification"

AI Assistant:
  → deploys into the existing solution (adas_deploy_skill)
  → redeploys (adas_redeploy)
  → confirms health

No context switching. No manual steps. The full ADAS platform — specs, validation, deployment, monitoring — is available as natural language.

How it reaches the AI community

ChatGPT users

ChatGPT supports MCP connectors in Developer Mode. Users connect by pasting a single URL:

Settings → Connectors → Developer Mode → paste https://mcp.ateam-ai.com

That's it. All 12 ADAS tools appear in ChatGPT. Any ChatGPT Pro, Plus, Business, or Enterprise user can build and deploy multi-agent solutions through conversation.

Claude users

Claude Desktop — install as an extension (one-click) or add to config:

{
  "mcpServers": {
    "ateam": {
      "command": "npx",
      "args": ["-y", "@ateam-ai/mcp"],
      "env": {
        "ADAS_TENANT": "your-tenant",
        "ADAS_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code — one command:

claude mcp add ateam -- npx -y @ateam-ai/mcp

Cursor / Windsurf / VS Code (Copilot)

Add to .cursor/mcp.json, mcp_config.json, or .vscode/mcp.json:

{
  "mcpServers": {
    "ateam": {
      "command": "npx",
      "args": ["-y", "@ateam-ai/mcp"],
      "env": {
        "ADAS_TENANT": "your-tenant",
        "ADAS_API_KEY": "your-api-key"
      }
    }
  }
}

Gemini and other platforms

As MCP adoption grows (it's now governed by the Agentic AI Foundation under the Linux Foundation, co-founded by Anthropic, OpenAI, and Block), every AI platform that implements MCP gets access to ateam-mcp automatically. The remote HTTP endpoint (https://mcp.ateam-ai.com) works with any client that supports Streamable HTTP transport.

Discovery

Developers find ateam-mcp through:

  • npm — npm search mcp ai-agents → @ateam-ai/mcp
  • Official MCP Registry — registry.modelcontextprotocol.io
  • Claude Desktop Extensions — built-in extension browser
  • Claude Code Plugin Marketplace — /plugin → Discover tab
  • Windsurf MCP Marketplace — built-in marketplace
  • VS Code MCP Gallery — Extensions view
  • Community directories — Smithery, mcp.so, PulseMCP (30,000+ combined listings)

Available tools

ToolWhat it does
adas_get_specRead the ADAS specification — skill schema, solution architecture, enums, agent guides
adas_get_examplesGet complete working examples — skills, connectors, solutions
adas_validate_skillValidate a skill definition through the 5-stage pipeline
adas_validate_solutionValidate a solution — cross-skill contracts + quality scoring
adas_deploy_solutionDeploy a complete solution to production
adas_deploy_skillAdd a skill to an existing solution
adas_deploy_connectorDeploy a connector to ADAS Core
adas_list_solutionsList all deployed solutions
adas_get_solutionInspect a solution — definition, skills, health, status, export
adas_updateUpdate a solution or skill incrementally (PATCH)
adas_redeployPush changes live — regenerates MCP servers, deploys to ADAS Core
adas_solution_chatTalk to the Solution Bot for guided modifications

Setup

# Clone
git clone https://github.com/ariekogan/ateam-mcp.git
cd ateam-mcp

# Install
npm install

# Configure
cp .env.example .env
# Edit .env with your ADAS tenant and API key

# Run
npm start

Architecture

┌─────────────────────────────────────────────┐
│  AI Environment                             │
│  (ChatGPT / Claude / Cursor / Windsurf)     │
│                                             │
│  Developer: "build me a support system"     │
└──────────────────┬──────────────────────────┘
                   │ MCP protocol
                   │ (stdio or HTTP)
┌──────────────────▼──────────────────────────┐
│  ateam-mcp                                  │
│  12 tools — spec, validate, deploy, manage  │
└──────────────────┬──────────────────────────┘
                   │ HTTPS
                   │ X-ADAS-TENANT / X-API-KEY
┌──────────────────▼──────────────────────────┐
│  ADAS External Agent API                    │
│  api.ateam-ai.com                           │
└──────────────────┬──────────────────────────┘
                   │
┌──────────────────▼──────────────────────────┐
│  ADAS Core                                  │
│  Multi-agent runtime                        │
└─────────────────────────────────────────────┘

License

MIT

Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
inference shell
inference shell
create and run specialised agents in minutes
build now →
MCP-ready Email SendingMCP-ready Email Sending
MCP-ready Email Sending
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Capacitor - Shared memory for your team’s coding agents.
Capacitor - Shared memory for your team’s coding agents.
Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →
CodeScene MCP ServerCodeScene MCP Server
CodeScene MCP Server
Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →
Give your AI the whole web as clean markdownGive your AI the whole web as clean markdown
Give your AI the whole web as clean markdown
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
belt - the only tool your agent needs
belt - the only tool your agent needs
belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
Categories
AI & LLM Tools
Registryactive
Package@ateam-ai/mcp
TransportSTDIO, HTTP
UpdatedFeb 17, 2026
View on GitHub

Related AI & LLM Tools MCP Servers

View all →
bch1212 avatar
Injectshield

bch1212/injectshield

Prompt-injection firewall for AI agents — scan untrusted text before LLM calls.
beforeyouship avatar
//beforeyouship — LLM cost modeling from your editor

beforeyouship/cost-model

Model the realistic monthly cost of an LLM app **before you build it**. Not a token calculator: retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth are modeled in, across GPT-5.x, Claude, Gemini, DeepSeek, and more. **Works without a key.** Connect and ask — demo mode covers the six free-tier models. A Pro API key ([beforeyouship.dev](https://beforeyouship.dev)) unlocks the full 18-model catalog. ## Tools | Tool | What it does | |---|---| - **`estimate_cost`** Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case $/mo per model, growth scenarios, and an opinionated recommendation. | - **`get_model_prices`** Current per-1M-token pricing (input, output, cached, batch) with context windows and staleness metadata. | - **`list_archetypes`** Seven preset architecture patterns (chatbot, RAG pipeline, multi-step agent, …) used as starting points for estimates. | ## Try it Paste into Claude Code or Cursor after connecting: > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day ## Setup ```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ``` ## Links - Docs & tool reference: https://beforeyouship.dev/docs#mcp - Live calculator: https://beforeyouship.dev - Announcement: https://beforeyouship.dev/blog/query-llm-costs-from-claude-code
beforeyouship avatar
//beforeyouship — LLM cost modeling from your editor

beforeyouship/cost-model-e50f1778

Model the realistic monthly cost of an LLM app **before you build it**. Not a token calculator: retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth are modeled in, across GPT-5.x, Claude, Gemini, DeepSeek, and more. **Works without a key.** Connect and ask — demo mode covers the six free-tier models. A Pro API key ([beforeyouship.dev](https://beforeyouship.dev)) unlocks the full 18-model catalog. ## Tools | Tool | What it does | |---|---| - **`estimate_cost`** Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case $/mo per model, growth scenarios, and an opinionated recommendation. | - **`get_model_prices`** Current per-1M-token pricing (input, output, cached, batch) with context windows and staleness metadata. | - **`list_archetypes`** Seven preset architecture patterns (chatbot, RAG pipeline, multi-step agent, …) used as starting points for estimates. | ## Try it Paste into Claude Code or Cursor after connecting: > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day ## Setup ```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ``` ## Links - Docs & tool reference: https://beforeyouship.dev/docs#mcp - Live calculator: https://beforeyouship.dev - Announcement: https://beforeyouship.dev/blog/query-llm-costs-from-claude-code
bitofacoder avatar
Omni Mcp Server

bitofacoder/omni-mcp-server

All-in-one MCP server: GitHub, Git, Slack, web fetch, memory, and filesystem. Agent Mode opt-in.
brunosrz avatar
Vectora

brunosrz/vectora

AI assistant with RAG, web search, filesystem and memory. MCP sub-agent for Claude Code.
bystray avatar
Gonka Network Pricing

bystray/gonka-mcp-server

Compare LLM inference costs vs OpenAI/Anthropic/DeepSeek. Gonka is up to 6800x cheaper.