LinkedIn Intelligence & Research MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| linkedin_research_profileA | Runs full end-to-end profile research, normalizes activity, extracts topics, detects signals, evaluates ICP match, and returns actionable outreach angles. |
| linkedin_analyze_profileC | Analyzes static profile headline, about section, experience, skills, and business positioning. |
| linkedin_analyze_postB | Performs a deep 15-dimension analysis on a single LinkedIn post (hook, topic, post type, pain points, tools, sentiment, commercial intent). |
| linkedin_detect_business_signalsA | Scans profile activity to discover growth, marketing, operational, and technical tracking signals (GA4, GTM, CAPI, Attribution). |
| linkedin_find_opportunitiesC | Identifies specific technical tracking or marketing service opportunities based on observed activity. |
| linkedin_extract_topicsB | Extracts top professional topics and mention frequencies from retrieved activity. |
| linkedin_build_lead_searchB | Translates business objectives into a structured LinkedIn lead search plan and Boolean queries. |
| linkedin_generate_boolean_searchB | Generates optimized Boolean search strings for LinkedIn People Search, Company Search, and Google X-ray. |
| linkedin_import_search_resultsA | Ingests JSON/CSV search result objects or profile URL lists into normalized Lead entities. |
| linkedin_analyze_search_resultsB | Categorizes, filters, and performs preliminary ICP scoring on an imported search result batch. |
| linkedin_filter_leadsC | Filters lead batches by minimum score, job title, location, business type, or active tracking opportunities. |
| linkedin_match_icpC | Evaluates lead fit against custom Ideal Customer Profile rules with confidence scoring. |
| linkedin_score_leadB | Scores a lead using the 100-point Lead Scoring Engine (ICP Fit, Service Relevance, Authority, Signals). |
| linkedin_rank_leadsB | Ranks and sorts imported lead batches by overall lead score, tracking opportunities, or intent. |
| linkedin_analyze_prospectB | High-level prospect analyzer orchestrating profile, company, signals, ICP matching, and lead scoring. |
| linkedin_create_lead_shortlistC | Generates a curated shortlist of top prospects (e.g. Top 20 PPC agency founders). |
| linkedin_get_recent_activityB | Retrieves normalized activity items over a specified date range. |
| linkedin_analyze_recent_activityC | Analyzes date-range activity, identifies recurring topics, priority shifts, and business signals. |
| linkedin_build_activity_timelineC | Constructs a chronological activity timeline summary. |
| linkedin_compare_activity_periodsA | Compares activity across two date periods (e.g. July vs. August) to identify strategy shifts, new topics, or disappearing themes. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| profile-analysis | Analyzes professional positioning and ICP match. |
| prospect-analysis | Evaluates lead score and outreach angles. |
| recent-activity-analysis | Analyzes recent date-range activity. |
| post-analysis | Runs 15-dimension post deep dive. |
| find-tracking-opportunities | Discovers GA4, GTM, CAPI, and attribution opportunities. |
| generate-lead-search | Generates Boolean search strings. |
| research-ppc-agency | Specialized research workflow for PPC agency decision-makers. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| res-profile | |
| res-profile-analysis | |
| res-activity | |
| res-timeline | |
| res-signals | |
| res-opportunities | |
| res-post | |
| res-company | |
| res-lead | |
| res-lead-score | |
| res-shortlist | |
| res-icp | |
| res-scoring-config | |
| res-signals-config |
TDQS
Scored across 20 tools
At least two pairs (research_profile vs analyze_prospect, build_lead_search vs generate_boolean_search) have heavily overlapping scopes, and extract_topics overlaps with analyze_recent_activity. Most other tools are clearly separated by noun and verb, so descriptions resolve most ambiguity, but the overlap is notable.
All 20 tools follow the linkedin_ prefix plus verb_noun snake_case pattern. Verbs are consistent lowercase and the noun indicates the target resource, making tool names highly predictable.
20 tools is on the upper end of typical server size, bordering on heavy. However, the tools form a coherent pipeline spanning activity retrieval, profile/post analysis, signal detection, lead search, scoring, and prospect orchestration, so the count is reasonably justified.
The server covers the full lead-research workflow: getting and analyzing activity, researching profiles, detecting signals, finding opportunities, building searches, importing/analyzing results, filtering/ranking, and scoring. Minor gaps include standalone company analysis or direct LinkedIn profile lookup, but these are workaroundable.