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lurq

Do these MCP servers coexist?

mcp_stack
Read-only

Check whether a set of MCP servers can be wired into one agent together. The npm question does not apply — servers are separate processes with nothing to resolve between them. They clash in the single flat TOOL NAMESPACE the agent assembles from all of them: two servers exposing the same tool name leave the agent unable to express which it means, and nothing errors, one simply shadows the other. Also reports the standing context cost, since every tool's schema rides in every request. Pass tools for a server when you already hold its tool list (any server: remote, PyPI, Docker, private) and it is analysed as-is; otherwise the npm server's probed surface is used, and one that has not been probed makes the answer UNKNOWN, never clean.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serversYesThe servers configured into one agent

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already mark it read-only and closed-world, but the description adds substantial non-obvious behavior: collisions fail silently with shadowing instead of erroring, context cost is accumulated per request, and an unprobed server yields UNKNOWN 'never clean'. Those are exactly the traits an agent cannot infer from structured fields.

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?

Front-loaded with the core question and free of filler, but it is a dense single paragraph packing four distinct ideas (namespace clash, context cost, tools override, UNKNOWN semantics). Slightly heavier than it needs to be, though every sentence carries information.

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

Completeness4/5

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

Single required parameter with full schema coverage and no output schema, so the burden on the description is modest. It covers the decisive edge case (UNKNOWN vs clean) and the reported context cost, though it never sketches the shape of the returned result.

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?

Schema description coverage is already 100%, so the baseline is 3; the description adds real meaning on top by explaining that `tools` can be passed for any server type (remote, PyPI, Docker, private) and is analyzed as-is rather than probed.

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 states a precise verb and resource — 'Check whether a set of MCP servers can be wired into one agent together' — and immediately scopes the concern to the flat tool namespace rather than npm dependency resolution. An agent can tell this apart from surface/diff/compat-style siblings without opening the schema.

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?

It gives a clear operative scenario (multiple servers destined for one agent) and an explicit branch for supplying `tools` versus relying on a probed npm surface. It does not, however, name a sibling alternative or state when a different tool would be the better pick.

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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