list_current_quantum_computersReturn the representative-entry table of current SOTA quantum computers (id, hardware type, physical qubit count, 2-qubit error rate). Same data that powers the website's "Current Quantum Computers" table.
| Name | Required | Description | Default |
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Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already provide the safety profile. The description adds context by specifying the exact fields returned (id, hardware type, physical qubit count, 2-qubit error rate) and that it mirrors the website table, which gives the agent a clear expectation of the data source and content. No contradictions; behavior is consistent with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, directly informative, no filler. Front-loaded with the main purpose and then adds provenance. Perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only tool, this description is complete: it specifies what is returned (fields), the source (website table), and implicitly the scope (current SOTA). The annotations cover safety properties, so no further behavioral detail is needed. The description is sufficient for an agent to select and use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the baseline is 4. The description goes slightly beyond the schema by specifying the returned fieldsced it adds no parameter-specific guidance, but none is needed. The mention of 'representative-entry table' clarifies that it's a summary, not exhaustive, which is useful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a representative-entry table of current SOTA quantum computers with specific fields (id, hardware type, qubit count, error rate). It distinguishes from siblings by focusing on 'current SOTA' and referencing the website's table, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context by indicating it returns the same data as the website's table, implying it is the canonical source for current quantum computer specs. However, it doesn't explicitly mention when not to use it or name alternative tools, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool has a clearly distinct role: forward expectation, inverse required error rate, multi-hardware comparison, fault-tolerant resource estimation, quantum volume rate, plus separate list/get/fit tools for hardware, historic data, algorithms, timings, and qLDPC codes. Cross-references in descriptions make selection unambiguous.
Tool names follow a predictable verb_noun pattern: compute_* for estimation operations, list_* for catalogs, get_* for retrieving specific data, plus compare_hardware_scenarios and fit_historic_series as clear descriptive exceptions. The naming style is consistent and readable.
Twelve tools is well-scoped for a quantum computing estimation and hardware comparison server. Each tool covers a distinct capability without redundancy, and the count feels appropriate for the domain's breadth.
The tool surface covers forward computation, inverse computation, multi-hardware comparison, fault-tolerant resource estimation, historical trends, current hardware catalogs, algorithm examples, hardware timings, and error-correction code data. There are no obvious dead ends; tools compose naturally to answer 'what hardware do I need and when will it exist?'.