Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Render tasks via Rube MCP (Composio): services, deployments, projects. Always search tools first for current schemas.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Automate Render cloud platform operations through Composio's Render toolkit via Rube MCP.
Toolkit docs: composio.dev/toolkits/render
RUBE_MANAGE_CONNECTIONS with toolkit renderRUBE_SEARCH_TOOLS first to get current tool schemasGet Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.
RUBE_SEARCH_TOOLS respondsRUBE_MANAGE_CONNECTIONS with toolkit renderWhen to use: User wants to find or inspect Render services (web services, static sites, workers, cron jobs)
Tool sequence:
RENDER_LIST_SERVICES - List all services with optional filters [Required]Key parameters:
name: Filter services by name substringtype: Filter by service type ('web_service', 'static_site', 'private_service', 'background_worker', 'cron_job')limit: Maximum results per page (default 20, max 100)cursor: Pagination cursor from previous responsePitfalls:
cursor until absentWhen to use: User wants to manually deploy or redeploy a service
Tool sequence:
RENDER_LIST_SERVICES - Find the service to deploy [Prerequisite]RENDER_TRIGGER_DEPLOY - Trigger a new deployment [Required]RENDER_RETRIEVE_DEPLOY - Monitor deployment progress [Optional]Key parameters:
serviceId: Service ID to deploy (required, format: 'srv-xxxxxxxxxxxx')clearCache: Set true to clear build cache before deployingserviceId: Service IDdeployId: Deploy ID from trigger response (format: 'dep-xxxxxxxxxxxx')Pitfalls:
serviceId is required; resolve via LIST_SERVICES firstclearCache: true forces a clean build; takes longer but resolves cache-related issuesWhen to use: User wants to check the progress or result of a deployment
Tool sequence:
RENDER_RETRIEVE_DEPLOY - Get deployment details and status [Required]Key parameters:
serviceId: Service ID (required)deployId: Deployment ID (required)status, createdAt, updatedAt, finishedAt, commitPitfalls:
serviceId and deployId are requiredWhen to use: User wants to list and organize Render projects
Tool sequence:
RENDER_LIST_PROJECTS - List all projects [Required]Key parameters:
limit: Maximum results per page (max 100)cursor: Pagination cursor from previous responsePitfalls:
Service name -> Service ID:
1. Call RENDER_LIST_SERVICES with name=service_name
2. Find service by name in results
3. Extract id (format: 'srv-xxxxxxxxxxxx')
Deployment lookup:
1. Store deployId from RENDER_TRIGGER_DEPLOY response
2. Call RENDER_RETRIEVE_DEPLOY with serviceId and deployId
3. Check status for completion
1. RENDER_LIST_SERVICES -> find service by name -> get serviceId
2. RENDER_TRIGGER_DEPLOY with serviceId -> get deployId
3. Loop: RENDER_RETRIEVE_DEPLOY with serviceId + deployId
4. Check status: 'live' = success, 'build_failed'/'update_failed' = error
5. Continue polling until terminal state reached
cursor from response for next pagecursor is absent or results are emptylimit to max (100) for fewer pagination roundsService IDs:
Service Types:
Deployment Behavior:
Rate Limits:
Response Parsing:
data key| Task | Tool Slug | Key Params |
|---|---|---|
| List services | RENDER_LIST_SERVICES | name, type, limit, cursor |
| Trigger deploy | RENDER_TRIGGER_DEPLOY | serviceId, clearCache |
| Get deploy status | RENDER_RETRIEVE_DEPLOY | serviceId, deployId |
| List projects | RENDER_LIST_PROJECTS | limit, cursor |
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概要と使いどころ
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
日本語の概要は準備中です。原文の説明を表示しています。
Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
日本語の概要は準備中です。原文の説明を表示しています。
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
日本語の概要は準備中です。原文の説明を表示しています。
Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。