Skip to main content
Glama

session_view_image

Retrieve images from visual memory by ID to enable LLM analysis. Returns Base64-encoded content for AI processing and interpretation of stored visuals.

Instructions

Retrieve an image from visual memory using its ID. Returns the image as Base64 inline content for the LLM to analyze. Use session_load_context first to see available image IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYesProject identifier.
image_idYesThe short image ID (e.g., '8f2a1b3c') from the visual memory index.
Behavior4/5

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

No annotations provided, so description carries full burden. Critically discloses return format 'Base64 inline content for the LLM to analyze' which compensates for missing output schema. Implies read-only nature via 'Retrieve' but doesn't explicitly confirm no side effects.

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?

Three sentences with zero waste: purpose (sentence 1), behavior (sentence 2), workflow guidance (sentence 3). Well-structured and front-loaded.

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

Completeness5/5

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

Appropriate for complexity level: 2 simple parameters with 100% schema coverage. Description compensates for missing output schema by detailing Base64 return format. No gaps given the tool's scope.

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

Parameters3/5

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

Schema has 100% description coverage (project and image_id fully documented). Description references 'its ID' but adds no semantic detail beyond what schema already provides. Baseline 3 appropriate when schema does heavy lifting.

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?

States specific verb (Retrieve) + resource (image from visual memory) + mechanism (using ID). Clear distinction from sibling session_save_image and session_search_memory tools.

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?

Explicitly states prerequisite workflow: 'Use session_load_context first to see available image IDs.' Provides clear sequencing guidance, though lacks explicit 'when not to use' exclusions.

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/dcostenco/BCBA'

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