FREE: extract text from an image URL via SaSame OCR (tesseract). Returns text preview + confidence. Full untruncated extraction is the paid x402 /ocr/full endpoint.
| Name | Required | Description | Default |
|---|---|---|---|
| image_url | Yes | Public URL of an image (png/jpg) to extract text from |
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?
The description discloses behavior beyond annotations: it states the tool is free, uses a specific OCR engine, returns a text preview and confidence score, and that full extraction requires payment. Annotations already indicate readOnlyHint=true and openWorldHint=true, and the description aligns with them, adding more depth about the tool's nature.
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?
The description is extremely concise, using two short sentences that front-load key information (FREE, action, algorithm). Every word is purposeful, with no redundancy or filler.
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?
Given the tool's simplicity (one param, no output schema, annotations present), the description provides sufficient context: what it does, what it returns, and how it relates to the paid version. It could mention supported image formats more explicitly, but the schema covers that. Overall, it is complete for an agent to select and use the tool.
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?
The input schema already provides 100% coverage for the single parameter 'image_url', describing it as a public URL for png/jpg images. The description does not add new semantic detail beyond emphasizing the URL aspect, so it meets the baseline expectation without exceeding it.
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 extracts text from an image URL via OCR, specifies the algorithm (SaSame OCR/tesseract), and distinguishes itself from the paid 'full' endpoint (x402 /ocr/full). This provides a specific verb and resource with sibling differentiation.
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?
The description explicitly frames the tool as free and contrasts it with the paid full extraction endpoint, giving clear context on when to use this version vs the alternative. It does not mention when not to use it among the listed sibling tools, but the paid alternative is effectively a sibling in the same API family.
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.
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.
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.
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.
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.