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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OCULAR_MODELYesVision-capable model name
MCP_HTTP_HOSTNoHTTP host binding127.0.0.1
MCP_HTTP_PATHNoHTTP path for MCP endpoint/mcp
MCP_HTTP_PORTNoHTTP port3000
MCP_TRANSPORTNoTransport mode (stdio or http)stdio
MCP_AUTH_TOKENNoAuth token for HTTP transport
OCULAR_API_KEYYesProvider API key
OCULAR_HEADERSNoOptional custom provider headers as JSON
MCP_AUTH_HEADERNoAuth header nameauthorization
MCP_AUTH_SCHEMENoAuth scheme (e.g., Bearer)Bearer
OCULAR_BASE_URLYesOpenAI-compatible API base URL
OCULAR_CACHE_DIRNoCache directory
OCULAR_MAX_TOKENSNoMaximum generated tokens
OCULAR_TIMEOUT_MSNoProvider timeout
OCULAR_TEMPERATURENoGeneration temperature
OCULAR_UPLOADS_DIRNoPersistent upload directory
OCULAR_MAX_IMAGE_MBNoMaximum image size
OCULAR_CACHE_ENABLEDNoEnable result cache
OCULAR_UPLOAD_URL_BASENoPublic base URL used in upload instructions

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}
prompts
{
  "listChanged": true
}
resources
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
analyze_imageB

Analyze a general image and return structured JSON for a coding agent.

extract_text_from_imageB

Extract OCR text from screenshots, documents, tables, terminal output, or code images.

analyze_ui_screenshotB

Analyze a webpage, app, UI, or design mockup screenshot for frontend implementation work.

diagnose_error_screenshotA

Analyze error, terminal, console, browser, or build failure screenshots.

compare_ui_screenshotsB

Compare two UI screenshots and return implementation-useful visual differences.

extract_table_from_imageC

Extract visible table data from an image as structured JSON, Markdown, or CSV-oriented output.

analyze_chart_imageB

Analyze a chart image and return labels, trends, approximate values, and limitations.

create_upload_sessionA

Returns upload instructions for the binary side channel (use this to analyze LOCAL image files without base64 corruption). Before uploading, verify the local file exists and is non-empty with Bash (e.g. ls -la <path> or test -f <path> && stat -c %s <path>). Then PUT the raw bytes to the returned upload_url with curl --data-binary (NOT base64); the response gives a file_id to pass to any vision tool. Stateless -- call once to learn the endpoint.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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