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bcharleson

Instantly MCP Server

get_server_info

Read-only

Retrieve server details including version, loaded categories, and configuration status to debug and verify setup for the Instantly.ai email outreach platform.

Instructions

Get Instantly MCP server information.

Returns server version, loaded categories, and configuration status. Useful for debugging and verifying server setup.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the get_server_info tool. It gathers server metadata, tool counts per category, API key status, lazy loading info, and rate limit details, then returns a formatted JSON string.
    async def get_server_info() -> str:
        """
        Get Instantly MCP server information.
        
        Returns server version, loaded categories, and configuration status.
        Useful for debugging and verifying server setup.
        """
        import json
        
        client = get_client()
        categories = get_requested_categories()
        
        info = {
            "server": SERVER_NAME,
            "version": SERVER_VERSION,
            "api_key_configured": client.has_api_key,
            "lazy_loading_enabled": is_lazy_loading_enabled(),
            "loaded_categories": categories,
            "tool_counts": {
                "accounts": 6 if "accounts" in categories else 0,
                "campaigns": 8 if "campaigns" in categories else 0,  # +2: delete_campaign, search_campaigns_by_contact
                "leads": 12 if "leads" in categories else 0,  # +1: delete_lead_list
                "emails": 6 if "emails" in categories else 0,  # +1: mark_thread_as_read
                "analytics": 3 if "analytics" in categories else 0,
                "background_jobs": 2 if "background_jobs" in categories else 0,
            },
            "total_tools": sum([
                6 if "accounts" in categories else 0,
                8 if "campaigns" in categories else 0,
                12 if "leads" in categories else 0,
                6 if "emails" in categories else 0,
                3 if "analytics" in categories else 0,
                2 if "background_jobs" in categories else 0,
            ]) + 1,  # +1 for get_server_info
            "rate_limit": {
                "remaining": client.rate_limit.remaining,
                "limit": client.rate_limit.limit,
                "reset_at": client.rate_limit.reset_at.isoformat() if client.rate_limit.reset_at else None,
            },
        }
        
        return json.dumps(info, indent=2)
  • The decorator that registers the get_server_info tool with the FastMCP server, specifying its name and readOnlyHint annotation.
    @mcp.tool(
        name="get_server_info",
        annotations={"readOnlyHint": True},
    )
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint=true, and the description aligns by describing a read operation ('Get'). It adds valuable context beyond annotations by specifying the return content (server version, loaded categories, configuration status) and the use case for debugging, which helps the agent understand the tool's behavior and output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, followed by specific return details and usage context in two additional sentences. Every sentence adds value without waste, making it efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, read-only, with output schema), the description is complete. It explains what the tool does, what it returns, and when to use it, covering all necessary aspects without needing to detail parameters or output structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters and 100% schema description coverage, the baseline is high. The description does not need to explain parameters, and it appropriately focuses on the tool's purpose and output, adding no redundant information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'Instantly MCP server information', specifying it returns server version, loaded categories, and configuration status. It distinguishes from sibling tools like get_account or get_campaign by focusing on server metadata rather than domain entities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit context for usage ('Useful for debugging and verifying server setup'), which helps the agent understand when to invoke this tool. However, it does not explicitly state when not to use it or name specific alternatives among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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