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weiwarren

AWS AgentCore MCP Server

by weiwarren
OverviewSchemaRelated ServersScoreDiscussions
Python

agentcore_observability

Monitor and debug AI agents in the AWS AgentCore framework to ensure performance and reliability through observability tools.

Instructions

Documentation on AgentCore Observability for monitoring and debugging agents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/aws_agentcore_mcp_server/server.py:45-50 (handler)
    The handler function for the agentcore_observability tool. Decorated with @mcp.tool() for automatic registration in the FastMCP server. Returns the content of the observability.md documentation file.
    @mcp.tool()
async def agentcore_observability() -> str:
    """Documentation on AgentCore Observability for monitoring and debugging agents."""
    return pkg_resources.joinpath("content", "observability.md").read_text(
        encoding="utf-8"
    )

Tool Definition Quality

C2.3/5.0
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. It vaguely suggests 'monitoring and debugging' but does not disclose behavioral traits such as whether it's read-only, requires authentication, has side effects, or involves rate limits. The lack of specifics makes it inadequate for understanding how the tool behaves.

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

Conciseness3/5

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

The description is a single, concise sentence, but it is under-specified rather than efficiently informative. It front-loads the topic but fails to provide actionable details, making it less helpful. While not verbose, it lacks the density of useful information that would warrant a higher score.

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 0 parameters, 100% schema coverage, and an output schema, the description's minimal content is partially acceptable. However, for a tool with no annotations and siblings, it should clarify purpose and usage more. It is incomplete as it leaves key behavioral and contextual gaps, but the structured data reduces the burden slightly.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, which is appropriate. A baseline of 4 is applied as it compensates for the lack of parameters by not introducing confusion, though it doesn't enhance parameter understanding beyond the schema.

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

Purpose2/5

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

The description 'Documentation on AgentCore Observability for monitoring and debugging agents' restates the tool name with minimal elaboration. It mentions 'monitoring and debugging' but lacks a specific verb (e.g., 'retrieve', 'configure') and resource (e.g., 'logs', 'metrics'), making it vague. It does not differentiate from siblings like agentcore_tools or agentcore_gateway, which could also relate to agent operations.

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

Usage Guidelines1/5

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 does not mention context, prerequisites, or exclusions, and there is no reference to sibling tools (e.g., agentcore_memory for memory-related tasks). This leaves the agent with no usage direction.

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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