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Kamy

by dev.kamy

Verify MCP server manifest

verify_mcp_server

Detect when an MCP server changes its tool manifest after you adopted it — the 'rug pull' case, where a server you already trusted silently rewrites a tool's description or input schema. Pass server_url and Kamy fetches that third-party server's manifest itself, or pass manifest when you already hold it (local or private servers). Returns status 'new' (first fingerprint for this account — nothing to compare against yet), 'unchanged', or 'mutated', plus a per-tool changes list with previous and current hashes. 'unchanged' means only that it matches what Kamy recorded previously; it is not a judgement that the server is trustworthy, and a first-ever 'new' result establishes a baseline rather than clearing anything. Requires a Kamy API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
manifestNoA tool manifest you already hold — the `tools/list` result, or an object with a `tools` array. Use this when the server isn't reachable from Kamy (local stdio server, private network). Supply either server_url or manifest.
server_urlNoURL of the MCP server to fingerprint. Kamy fetches its tool manifest server-side. Supply either server_url or manifest.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description discloses that the tool records fingerprints ('first fingerprint for this account'), explains the meaning of each status, and explicitly warns that 'unchanged' is not a trust judgement. It also states the API key requirement, adding transparency about auth needs.

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

Conciseness5/5

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

The description is compact yet dense, covering purpose, parameter selection, return statuses, caveats, and auth in about five sentences. No filler or redundancy; each sentence contributes essential information.

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?

For a tool with no output schema and an external-fetch+state-recording behavior, the description fully covers the return format, semantics, and prerequisites. It even explains first-run behavior and the non-judgemental nature of 'unchanged', leaving no major gaps.

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 schema already describes both parameters, so the baseline is 3. The description adds value by explaining the selection logic: 'Pass server_url and Kamy fetches... or pass manifest when you already hold it (local or private servers)'—this provides practical guidance beyond the schema's 'Supply either' note.

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 opens with a specific verb+resource: 'Detect when an MCP server changes its tool manifest after you adopted it'. It clearly distinguishes this from sibling verification tools (e.g., verify_pdf_signature, verify_attestation) by focusing on manifest mutation.

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?

The description gives clear context for when to use it (after adopting a server, to check for 'rug pull' manifest changes) and explains the two input modes (server_url for Kamy to fetch, manifest for local/private servers). It doesn't explicitly name alternatives, but the context is clear enough.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct action or resource with minimal ambiguity. For example, `render_pdf`, `render_docx`, `render_xlsx`, and `pptx` are clearly different output formats, while `merge_pdfs`, `split_pdf`, and `edit_pdf` target different PDF operations. The signature tools (`create_signature_request`, `get_signature_request`, etc.) are also clearly separated by lifecycle stage. No two tools appear to do the same thing.

Naming Consistency5/5

Tool names follow a highly consistent `verb_noun` pattern throughout, such as `create_signature_request`, `get_signature_request`, `list_signature_requests`, and `remind_signature`. This pattern is applied uniformly across all major domains (render, signature, template, webhook, trace), making the API predictable and easy for an agent to navigate.

Tool Count4/5

With 59 tools, this is a large surface area, but it is justified by the breadth of functionality: document rendering in multiple formats, e-signatures, template management, webhooks, scheduling, and a crypto/audit trail. While large, each tool has a distinct purpose, and the count feels appropriate for the scope of a comprehensive document automation API. A surface this large risks being overwhelming, but the internal organization is logical.

Completeness5/5

The tool surface is remarkably complete, covering the full lifecycle for multiple domains. For e-signatures, there are tools for CRUD (requests, templates), sending (individual, bulk, envelope), monitoring (get, list), reminders, and certificates. For documents, it covers creation, conversion, editing, merging, splitting, and verification. The inclusion of utility tools like `get_started`, `validate_payload`, and the audit trail tools further solidifies this as a well-considered, production-ready API surface.

Resources