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Claude Code
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Grok
Grok Bot+18 agentsMCP Server Architect
Give it your API and your use case; it returns an MCP design that works in practice, not just in a demo.
$19
MCP Server Architect
Example session with this skill installed
We have a REST API for our project-management tool with about 60 endpoints covering projects, tasks, comments, users and labels. We want an MCP server so Claude can triage and update tasks for a user. Auth is OAuth2 with per-user tokens.
- Read your context and instructions
- Compiled the mcp server architect
MCP tool surface for task triage: 60 endpoints consolidated into 6 task-first tools, with curated responses and per-user OAuth.
Tool surface
| Tool | Wraps | Purpose |
|---|---|---|
find_tasks | list tasks, labels, users | Search by text, status, assignee, label |
get_task | task, comments, labels | One call for full context |
update_task | status, assignee, labels, due date | Single edit tool |
add_comment | comments | Leave a triage note |
create_task | tasks | New task in a project |
list_projects | projects | Pick a project by name |
Schema and description (written as a prompt)
{ "name": "update_task",
"description": "Change a task's status, assignee, labels or due date. Use find_tasks first to get the task_id. Only pass fields you want to change.",
"inputSchema": { "type": "object", "required": ["task_id"],
"properties": { "task_id": {"type": "string"},
"status": {"enum": ["todo","in_progress","blocked","done"]},
"assignee_email": {"type": "string"} } } }
Response curation
Return id, title, status, assignee, labels and a short comment summary. Drop internal IDs, audit fields and HTML bodies. Cap lists and return a cursor.
Auth
Use the MCP authorization flow with OAuth2 so each call runs with the user's own token. Never share a service token.
Next steps
- Map each tool to its underlying endpoints
- Test descriptions with real triage prompts
Connects securely to your tools. The creator never sees your data.
About this skill
The default MCP server is an API wrapper that dumps forty endpoint-shaped tools on the model and hopes — and the model gets confused, picks the wrong tool, and produces garbage that looks like a tool call. Good MCP design is a different craft: composing tools at the right abstraction level (not too granular, not too broad), writing descriptions the model actually uses to pick correctly, designing the resource and prompt primitives that make your server genuinely useful rather than technically compliant, and handling the auth and error surface that breaks most MCP integrations in production. This skill architects your MCP server from the tool inventory up: what tools to expose, how to describe them, what to bundle vs. split, how to handle state across calls, and how to test that the model actually uses it correctly. Give it your API and your use case; it returns an MCP design that works in practice, not just in a demo.
- Does not provide hosting or deployment services.
- Requires user to provide API documentation or endpoint lists.
- Focused on architecture, not boilerplate code generation.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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