Skip to main content
Glama

upload_media

Upload local media files to receive dp:// references, enabling their use in survey descriptions for annotation tasks.

Instructions

Upload local media files (images, audio, video) and return dp:// references.

Use this BEFORE plan_survey / create_survey whenever the user wants a survey over local files — annotators cannot reach file:// paths or local disk, and the server rejects non-dp:// / non-https:// URLs.

After uploading, pass the returned dp:// refs verbatim in the plan_survey description so the generated plan references the uploaded media. Example:

refs = upload_media(["/tmp/a.png", "/tmp/b.png"])
# → dp://media/abc123.png and dp://media/def456.png
plan_survey(
    description="Compare design A (dp://media/abc123.png) against "
                "design B (dp://media/def456.png). Target: UX designers.",
    max_responses=10,
)

Already-hosted public https:// URLs do NOT need uploading — you can reference them directly in the description.

Args: file_paths: List of absolute local paths to media files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are present, so the description carries full burden. It explains the upload process, return format (dp:// refs), constraints (server rejects non-dp:///non-https://), and workflow integration. However, it does not mention potential limitations like file size, permissions, or failure modes, which prevents a higher score.

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 concise and well-structured: a clear purpose statement, followed by usage context, an example, and an exception. Every sentence adds value, and the example concretely illustrates the intended pattern.

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?

Given that an output schema exists (mentioned in context), the description adequately covers the return value (dp:// refs) via text and example. It also clearly relates to sibling tools (plan_survey, create_survey). No critical information is missing for an AI agent to use this tool correctly.

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

Parameters5/5

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

The schema has one parameter with no description coverage. The description adds significant meaning by stating that file_paths must be an array of absolute local paths to media files. This clarifies the expected format and domain beyond the simple 'string' type.

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 clearly states the verb (upload), resource (local media files), and output (dp:// references). It specifies supported types (images, audio, video) and distinguishes itself from other tools by being a prerequisite for plan_survey/create_survey when dealing with local files.

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 explicitly advises to use this tool before plan_survey/create_survey for any survey over local files, and notes that public https URLs do not need uploading. This provides clear when-to-use and when-not-to-use guidance, and explains the rationale (annotators cannot access local disk).

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/impel-intelligence/datapoint-mcp'

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