Skip to main content
Glama

analyze_image

Analyze a single image from a local path, URL, or data URL using specialized modes (OCR, document, chart, code) to provide image understanding to text-only agents.

Instructions

DO NOT CALL if you natively support vision and can access the supplied image directly. Call this MCP only when native vision is unavailable, the image source is inaccessible to your native vision capability, or the user explicitly requests this MCP or its configured provider.

Analyze one local image path, HTTP(S) image URL, or image data URL. This CLI-friendly single-image tool is the simplest entry point for mcporter and shell automation. Use understand_image for multiple images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoauto
imageYes
detailNoauto
promptNoAnalyze the supplied image.
ascii_modeNoauto
max_tokensNo
system_promptNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does add context about supported image source types and the single-image limitation. However, it does not disclose return format, how modes affect processing, or potential errors, leaving behavioral expectations partially unclear.

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 well-structured, front-loading the critical DO NOT CALL warning, followed by a concise function statement and sibling distinction. Every sentence serves a purpose with no unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description needs to explain return values and parameter behaviors. It provides essential usage guidelines but omits output semantics and details for six of seven parameters, making it incomplete for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description only explains the image parameter (path, URL, data URL). The other six parameters (mode, detail, prompt, ascii_mode, max_tokens, system_prompt) receive no explanation, creating significant ambiguity for correct use.

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 explicitly states the tool analyzes a single image from a path, URL, or data URL. It clearly distinguishes from the sibling tool by noting 'Use understand_image for multiple images,' making the purpose specific and unambiguous.

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?

The description opens with explicit DO NOT CALL conditions, then provides clear criteria for when to call (native vision unavailable, source inaccessible, or user requests the MCP/provider). It also names the alternative for multiple images, giving comprehensive when/when-not guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/weekitmo/vision-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server