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Reach MCP — LinkedIn for AI agents

upload_media_from_url

Upload an image to LinkedIn by fetching it from a public URL. Returns a digitalmediaAsset URN (urn:li:digitalmediaAsset:…) that can be passed to create_post (single image) or create_multi_photo (multi-photo). Use this instead of upload-media when working as an agent — no binary file upload needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_urlYesPublicly accessible URL of the image to upload.
account_idYesReach id of the LinkedIn account to act on, from list_accounts.
idempotency_keyNoOptional. A key you choose (a UUID is fine) that names this exact call. If you retry with the same key and the same arguments, the first call's result is returned and nothing is done twice on LinkedIn. Reusing a key with different arguments is refused. Keys expire after 24 hours.
media_upload_typeNoLinkedIn media upload type (default: IMAGE_SHARING).IMAGE_SHARING

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urnNourn:li:digitalmediaAsset:… to pass as media_urn

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the mutating nature is already known. The description adds meaningful context: the mechanism (fetching from a public URL, no binary upload) and the downstream URN usability. It does not contradict annotations, but does not disclose potential nuances like rate limits or the side-effect of fetching a remote URL.

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?

Two sentences carry all essential information: the core action, the output, downstream usage, and an alternative tool, all without wasted words. The sentence is front-loaded and easy to parse.

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?

With a rich output schema, 100% parameter coverage, and annotations present, the description adds the missing behavioral and usage context: the URL-fetching mechanics, the URN's role, and the alternative. Nothing needed for a correct agent invocation appears to be missing.

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 description coverage is 100%, so the parameters (image_url, account_id, idempotency_key, media_upload_type) are already fully documented in the schema. The description reiterates 'public URL' and 'fetching' but adds no new parameter behavior beyond what the schema provides. Baseline 3 is appropriate.

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 states a specific verb and resource: 'Upload an image to LinkedIn by fetching it from a public URL.' It also distinguishes the tool from alternatives by naming the output (a digitalmediaAsset URN) and pointing to downstream tools (create_post, create_multi_photo). An agent can identify the tool's purpose and scope immediately.

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 says to use this instead of upload-media when working as an agent, noting the reason (no binary file upload needed). It also clarifies how the URN output fits into the broader workflow with create_post and create_multi_photo, giving the agent clear context on when to choose this tool.

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

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