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Glama

SaSame MCP Observatory + Gold Rush Town

by online.sasame

subscribe_grade_changes

Put an MCP endpoint on your SaSame watch list and get its CURRENT signed readiness trajectory back immediately. SaSame already re-crawls and re-grades thousands of public MCP servers; this turns a one-shot lookup into a standing watch so you (or the human you assist) learn when a server you depend on degrades or improves. Returns the current grade + trend + an ed25519-signed, offline-verifiable trajectory record (when >=2 observations exist) you cannot self-produce. Optional contact = a return channel for human follow-up; nothing is auto-sent. Free, read of the proprietary longitudinal ledger.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoOptional: why you are watching it / what change matters to you.
targetYesThe MCP endpoint URL to watch, e.g. https://example.com/mcp
contactNoOptional return channel (agent URL / email / callback). Stored for follow-up, never auto-contacted.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations indicate not read-only and not destructive. The description adds that it is a free read of a proprietary ledger, stores contact info without auto-contacting, and returns a signed trajectory. It lacks details on update frequency or push mechanism but covers key behaviors.

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 concise, front-loads the core action and immediate result, then adds context and details. Every sentence earns its place with no waste.

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?

No output schema exists, so the description explains return values (grade, trend, signed trajectory). It covers the main purpose and data returned. Missing details like update frequency or error handling, but sufficient for a subscription tool.

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 covers 100% of parameters with descriptions. The tool description adds context for each parameter: target as endpoint URL, note as reason, contact as return channel stored but not auto-contacted. This adds value beyond schema.

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 clearly states the tool subscribes to grade changes for an MCP endpoint, returning immediate current grade and trend. It distinguishes from one-shot lookups by emphasizing standing watch functionality.

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 implies usage for monitoring server grade changes over time, contrasting with one-shot lookups. It does not explicitly list alternatives or exclusions, but context is clear.

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

B3.1/5.0
Disambiguation2/5

With 94 tools spanning overlapping concepts (multiple readiness/audit/grade tools, many status checkers, deprecated aliases like trust_* vs observation_*), agents will frequently struggle to pick the right one. While each tool is individually distinct, the sheer volume and conceptual overlap (e.g., audit_mcp, readiness_report, verify_mcp_ready, lookup_readiness, recommend_mcp, subscribe_grade_changes) create high misselection risk.

Naming Consistency3/5

Most tools use snake_case with underscores, but the pattern is inconsistent: some are verb-first (audit_mcp, verify_mcp_ready, claim_start, check_engagement) while others are noun-first (receipt_issue, meter_open, work_order_open, agent_invoice_status). Deprecated aliases like trust_compare vs observation_compare further break consistency, though the majority remain readable.

Tool Count1/5

94 tools is far beyond any reasonable scope for a single server, even one with broad ambitions like 'observatory + town'. The calibration notes 50+ as extreme mismatch; this server far exceeds that. Many tools are highly specific (e.g., factory_resolve_dead_letter, visit_touch_status, start_here) and could be consolidated or split into separate servers.

Completeness3/5

The server covers a wide range of domains (auditing, claiming, receipts, meters, escrow, work orders, gold rush, town, analytics) and offers many CRUD-like operations, but several lifecycle gaps exist: no cancel/close for work orders (only open/accept/deliver/accept_delivery), escrow (only open/attest/status), or meters (only open/charge/status). Given the massive scope, important operations are missing, though core workflows are present.

Resources