Image Parse MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| IMAGE_PARSE_MODEL | No | Multimodal model name | gpt-4o |
| IMAGE_PARSE_API_KEY | Yes | API key for your provider | |
| IMAGE_PARSE_BASE_URL | No | API base URL | https://api.openai.com/v1 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_imageA | Analyze an image with a multimodal LLM (GPT-4o, Claude, Gemini, etc.). Provide an image (URL, local path, or base64) and a description of what you want to know. The tool calls an OpenAI-compatible vision API and returns the model's text response. Use this tool whenever you have an image and need to:
Args: params (AnalyzeImageInput): - image_source (str): URL, local file path, or base64 image data. - prompt (str): What to analyze or extract from the image. - mime_type (Optional[str]): Override auto-detected MIME type. Returns: str: The multimodal model's analysis as plain text / Markdown. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap. Agents can unambiguously select the correct tool for any image analysis task.
The single tool uses a clear verb_noun pattern ('analyze_image'), which is consistent with best practices. No other tools exist to introduce inconsistency.
One tool is on the low end for a general utility, but it fits the narrow scope of image parsing via LLM. A single unified tool can be sufficient if it covers the intended use cases without needing multiple specialized tools.
The tool covers core image analysis needs (description, OCR, chart understanding) through a multimodal LLM. Minor gaps like batch processing or model selection are absent, but the core functionality is well-covered for the stated purpose.