Skip to main content
Glama
DeepaRajareddy

Redshift MCP Server

by DeepaRajareddy
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

redshift_connection_status

Check the connection status of Amazon Redshift databases to verify connectivity and ensure database operations can proceed.

Instructions

Check the Redshift connection status.

Returns:
    Connection status information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • redshift_mcp_server.py:133-154 (handler)
    The handler function for the 'redshift_connection_status' tool. It is decorated with @mcp.tool() for registration and implements the logic to check Redshift connection status, returning JSON with status details.
    @mcp.tool()
def redshift_connection_status() -> str:
    """
    Check the Redshift connection status.
    
    Returns:
        Connection status information
    """
    try:
        with get_connection() as conn:
            return json.dumps({
                "status": "connected",
                "host": REDSHIFT_HOST,
                "port": REDSHIFT_PORT,
                "database": REDSHIFT_DATABASE
            }, indent=2)
    except Exception as e:
        return json.dumps({
            "status": "disconnected",
            "error": str(e)
        }, indent=2)

Tool Definition Quality

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Checks' and 'Returns connection status information', which implies a read-only, non-destructive operation, but doesn't specify what 'status information' includes (e.g., connectivity, latency, error details), whether it requires authentication, or any rate limits. For a tool with zero annotation coverage, this is insufficient.

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

Conciseness4/5

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

The description is very concise with two short sentences that are front-loaded: the first states the purpose, and the second clarifies the return. There's no wasted text, but it could be slightly more structured (e.g., bullet points for return details) without losing efficiency.

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

Completeness3/5

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

Given the tool's low complexity (0 parameters) and the presence of an output schema (which should document return values), the description is minimally adequate. However, it lacks context about when to use it versus siblings, and without annotations, it doesn't fully disclose behavioral traits like error handling or authentication needs, leaving gaps for an AI agent.

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?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it appropriately avoids discussing inputs. Since there are no parameters, a baseline score of 4 is justified as the description doesn't introduce confusion or redundancy.

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

Purpose4/5

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

The description clearly states the tool's purpose as 'Check the Redshift connection status' with a specific verb ('Check') and resource ('Redshift connection status'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'redshift_query' or 'redshift_list_tables' in terms of when to use this specific connection check versus other Redshift operations.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether a connection must be established first), typical use cases (e.g., diagnostic checks before querying), or exclusions. With sibling tools like 'redshift_query' available, the lack of contextual guidance is a clear gap.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DeepaRajareddy/redshift_mcp_server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server