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discover_tool_input_values

Read-only

Find exact input values a tool requires from bundled reference data before calling it, preventing guessed identifiers and errors; works offline.

Instructions

Find the exact input values a specific tool requires, from reference data bundled with this server.

Call this BEFORE calling a tool that needs an exact identifier you do not already know. Do not guess the identifier and do not browse the Couchbase documentation website for it -- a guessed value comes back from the target tool as an error with no data. The reference data ships inside this server, so this works offline and while the cluster is unreachable, which is exactly when you are most likely to be looking up a metric name.

Registered today:

  • tool_name="get_cluster_metrics" -> every Couchbase Server metric name, with its type (counter/gauge/histogram), unit, the server version it first appeared in, and a one-line description. Feed a result's "name" straight into get_cluster_metrics.

tool_name is the only required argument; everything else is optional.

Two ways to call it:

  1. Browse -- pass tool_name alone. Every registered dataset is currently treated as too large to list in full, so this returns "record_count", a small "sample_records" preview, the "chapters" block (the small set of fields you can filter on, with every legal value and a record count each), and a "next_step" pointing you at search instead of a partial list.

  2. Search -- pass tool_name and search_keywords. Returns records ranked by fuzzy relevance, best first. Matching is fuzzy over identifiers and descriptions, so partial words and near-misses still hit.

Every response includes the chapters block, so you never need a separate browse call before narrowing.

Input Schema

NameRequiredDescriptionDefault
min_scoreNoRelevance floor, 0-100. Defaults to 0, meaning nothing is filtered out and you always get the best max_results matches ranked by score, however weak. Check each result's "score" to judge quality -- low scores across the board mean your keywords missed, so change them rather than reading further down the list. Raise this only to suppress weak matches you have already seen.
tool_nameYesREQUIRED. The tool you are about to call, e.g. "get_cluster_metrics". An unrecognised value returns the list of registered names, so you do not need to guess twice.
max_resultsNoHow many records to return. NOT capped by this server -- you are responsible for choosing a value whose response fits your client's output-size limit. If results are too broad, add keywords or a chapter filter rather than raising this.
chapter_filtersNoOptional narrowing, as {chapter_field: value}, e.g. {"category": "Query Service Metrics"}. Only fields listed in the response's "chapters" are accepted (a dataset without chapters accepts none), and multiple filters are combined with AND. Strongly recommended when you know the service: identifiers use short prefixes (kv_, n1ql_, fts_) that keyword search cannot connect to service names, so an unfiltered search for "query service memory" can return Index Service metrics instead.
search_keywordsNoA LIST of words describing what you are looking for, e.g. ["disk", "write", "queue"] or ["index", "resident", "ratio"]. Keep each concept a separate list item. Omit to browse instead of searching.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true, so the description carries the rest, and it does: offline operation while the cluster is unreachable, an unrecognized tool_name returning the registered-name list instead of failing, max_results being uncapped by the server, and score-based ranking with guidance on interpreting weak scores. It is consistent with the read-only annotation and adds substantial operational context.

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 critical instruction (call before the target tool, don't guess) is front-loaded, and the two-call-mode breakdown is easy to scan. It runs long for a lookup helper and repeats the chapters-points-to-search idea in both the browse section and the closing sentence, which is mild redundancy rather than harm.

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?

An output schema exists, so return values need no explanation, yet the description still summarizes the response shape (record_count, sample_records, chapters, next_step) precisely enough to tell an agent not to expect a full list from a browse call. For a five-parameter read-only lookup tool, nothing an agent needs in order to call it correctly is missing.

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 coverage is 100% and the schema descriptions are already detailed, so the baseline is 3; the description earns an increment by explaining the mutually exclusive browse-vs-search call patterns and noting that tool_name is the only required argument. It stops short of adding anything new about min_score or max_results beyond what the schema already says.

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 uses a specific verb+resource formulation: find exact input values for a named tool from reference data bundled with the server. It also names the downstream consumer ("get_cluster_metrics") and the concrete payload (metric name, type, unit, version, description), so an agent can tell immediately this is a lookup tool, not a cluster query tool like its siblings.

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

Usage Guidelines5/5

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

It states the trigger explicitly ("Call this BEFORE calling a tool that needs an exact identifier you do not already know"), names two anti-patterns to avoid (guessing, browsing the Couchbase docs site), and explains the cost of getting it wrong (the target tool errors with no data). It also routes between its own two modes: tool_name alone to browse, tool_name plus search_keywords to search.

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