code

Ai Specialists

Verified

by erikashby

Call the MCP endpoint via HTTP POST. The endpoint URL is stored in TOOLS.md or provided by the user. ```bash curl -s -X POST "$MCP_URL" \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"TOOL_NAME","arguments":{...}}}' ``` **Critical headers:** Must include `Accept: application/json, text/event-stream` or the server returns 406. **Response format:** SSE — parse with: `response.split('data:

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AI Specialists Hub - MCP Integration

Connection

Call the MCP endpoint via HTTP POST. The endpoint URL is stored in TOOLS.md or provided by the user.

curl -s -X POST "$MCP_URL" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"TOOL_NAME","arguments":{...}}}'

Critical headers: Must include Accept: application/json, text/event-stream or the server returns 406.

Response format: SSE — parse with: response.split('data: ')[1] → JSON → result.content[0].text

Available Tools

Discovery & Management

| Tool | Required Params | Description |

|------|----------------|-------------|

| list_specialists | — | List all hired specialists |

| list_specialist_types | — | List available specialist types |

| hire_specialist | type, name | Hire a new specialist |

| dismiss_specialist | specialist | Remove a specialist |

| import_specialist | url | Import from GitHub URL |

| get_specialist_overview | specialist | Get specialist summary |

Workspace Navigation

| Tool | Required Params | Description |

|------|----------------|-------------|

| explore_specialist_tree | specialist | Full folder/file tree |

| list_specialist_folder | specialist, folder_path | List folder contents |

Document Operations

| Tool | Required Params | Description |

|------|----------------|-------------|

| read_specialist_document | specialist, document_path | Read one document |

| read_specialist_documents | specialist, document_paths (array) | Bulk read multiple docs |

| update_specialist_document | specialist, document_path, content | Create or update a doc |

| delete_specialist_document | specialist, document_path | Delete a document |

Folder Operations

| Tool | Required Params | Description |

|------|----------------|-------------|

| create_specialist_folder | specialist, folder_path | Create folder (recursive) |

| delete_specialist_folder | specialist, folder_path | Delete folder and contents |

Parameter note: The specialist identifier is always the id field from list_specialists, not the display name. Use lowercase (e.g. ruby, peter, benjamin).

Working with a Specialist

Every specialist has an ai-instructions/ folder containing their identity and behavioral instructions. Always read these first when working with a specialist you haven't loaded yet:

ai-instructions/
├── core-instructions.md    # Who they are, what they do, how they behave
└── getting_started.md      # Initialization sequence, workspace structure

Pattern: First interaction with a specialist

  1. list_specialists → find the specialist id
  2. read_specialist_documents → read ai-instructions/core-instructions.md and ai-instructions/getting_started.md
  3. Understand their domain, workspace structure, and communication style
  4. explore_specialist_tree → see their full workspace
  5. Now you can work with their data informed by their context

Pattern: Quick data retrieval

  1. explore_specialist_tree → find the files you need
  2. read_specialist_documents → bulk read (more efficient than individual reads)
  3. Summarize for the user

Pattern: Updating specialist data

  1. Read the existing document first
  2. Modify content as needed
  3. update_specialist_document → write back (creates if new, overwrites if existing)
  4. For new folders: create_specialist_folder first, then write documents into it

User Signup (Agent-Initiated Onboarding)

If your human doesn't have an AI Specialists Hub account yet, you can create one via the public signup API:

curl -s -X POST "https://aispecialistshub.com/api/v1/signup" \
  -H "Content-Type: application/json" \
  -d '{"username":"<username>","email":"<email>","password":"<password>"}'

Response (201):

{
  "username": "...",
  "mcpKey": "...",
  "accountStatus": "unverified",
  "specialistLimit": 2,
  "message": "..."
}

⚠️ CRITICAL: Credential Handoff

You MUST provide all credentials to the human. Whether you auto-generate the username/email/password or ask the human to choose them, the human must receive:

  1. Username — for web dashboard login at aispecialistshub.com
  2. Email — used for account verification
  3. Password — for web dashboard login
  4. MCP key — for connecting AI tools to their specialists

Never keep credentials from the human. They own the account. Present all four clearly after signup.

Unverified Accounts

  • Limited to 2 specialists (default: Friday is auto-hired)
  • Full MCP access — specialists work immediately
  • Can log in to web dashboard with username/password
  • Verify email for full access (more specialists)

Signup Flow

  1. Confirm the human wants an AI Specialists Hub account
  2. Collect or generate: username, email, password
  3. Call POST /api/v1/signup
  4. Give the human ALL credentials (username, email, password, MCP key)
  5. Store the MCP endpoint URL in your config: https://aispecialistshub.com/api/v1/mcp/<username>/<mcpKey>
  6. Start using specialists via MCP

Configuration

Store the MCP endpoint URL in TOOLS.md:

### AI Specialists Hub
- MCP endpoint: https://aispecialistshub.com/api/v1/mcp/<user>/<key>

See references/specialists-guide.md for details on specialist workspace conventions.