LinkedIn Ad Library MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| HOST | No | HTTP server bind address | 127.0.0.1 |
| MCP_PORT | No | HTTP server port | 3000 |
| RATE_LIMIT | No | Max requests per minute (HTTP mode) | 100 |
| MCP_TRANSPORT | No | Transport mode: stdio or http | stdio |
| LINKEDIN_ACCESS_TOKEN | Yes | OAuth access token for LinkedIn Ad Library API |
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": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_adsA | Search LinkedIn sponsored ads by keyword, company, or topic. Use to analyze competitor ad copy, messaging strategy, creative formats, geo-targeting, and audience segmentation. Returns: advertiser name and payer, ad type (video, image, document, status update), impression ranges, country distribution (%), targeting facets (language, location, job title, company, audience), and direct link to the ad. Example: search_ads({ keyword: "klarna", count: 25 }) |
| search_jobsA | Search LinkedIn sponsored job postings. Use to track competitor hiring patterns, team expansion signals, and market positioning through the roles they're investing in. Returns: job title, organization, location, payer (who's paying for the sponsorship), and description preview. Example: search_jobs({ keyword: "fintech product manager", count: 25 }) |
| search_paid_endorsementsA | Search LinkedIn thought leader ads (paid endorsements). Use to identify influencer partnerships, executive branding strategies, and creator-driven campaigns by competitors. Returns: direct URLs to the sponsored posts. Example: search_paid_endorsements({ keyword: "scalapay" }) |
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 3 tools
Each tool targets a distinct category: sponsored ads, jobs, and paid endorsements. There is no overlap between the search functions, and the descriptions clearly differentiate their purposes.
All tool names follow a consistent 'search_' + noun pattern, making the set predictable and easy to navigate. The naming convention is uniform across all three tools.
Three tools is minimal but appropriate for the server's narrow scope—it covers the three main segments of LinkedIn's Ad Library. While slightly thin, each tool serves a clear and necessary function.
The set covers the primary ad types available in LinkedIn's Ad Library: regular ads, jobs, and thought leader ads. It provides comprehensive search results for each, though more granular detail endpoints (e.g., fetch by ID) are missing, but they are not essential for typical competitor analysis.