social-research-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APIFY_TOKEN | Yes | Apify API token for scraping | |
| OPENAI_API_KEY | No | OpenAI API key for timeline embeddings (semantic search) | |
| SOCIAL_RESEARCH_PORT | No | HTTP port | 3847 |
| SOCIAL_RESEARCH_DATA_DIR | No | Data directory | ~/.social-research-mcp/data/ |
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 |
|---|---|
| scrape_twitterB | Scrape tweets from Twitter/X. Search by query, hashtag, or user timeline. Results are saved to the local timeline database for later analysis. |
| scrape_instagramC | Scrape posts from Instagram. Search by URL, hashtag, or keyword. Results are saved to the local timeline database. |
| scrape_tiktokB | Scrape videos from TikTok. Search by profile, hashtag, or keyword. Results are saved to the local timeline database. |
| scrape_youtubeC | Scrape videos from YouTube. Search by keyword or channel URL. Results are saved to the local timeline database. |
| scrape_linkedinC | Scrape posts from LinkedIn. Search by profile URL, company URL, or keyword. Results are saved to the local timeline database. |
| scrape_facebookB | Scrape posts from Facebook pages. Search by page URL or keyword. Results are saved to the local timeline database. |
| scrape_redditB | Scrape posts from Reddit. Search by subreddit, keyword, or direct URL. Results are saved to the local timeline database. |
| timeline_searchA | Semantic search across your timeline database. Uses AI embeddings to find posts by meaning, not just keywords. Requires OPENAI_API_KEY. |
| timeline_queryC | Structured query against the timeline database. Filter by platform, date, engagement, author, or hashtags — no AI needed. |
| timeline_trendsB | Detect trending topics across your stored timeline data. Identifies spikes in hashtag/keyword frequency and sentiment shifts. |
| timeline_statsB | Get aggregate statistics from your timeline: total posts by platform, avg engagement, most active authors, top hashtags. |
| analyze_profileB | Analyze a social media profile: scrape recent posts and compute engagement rate, posting frequency, content themes, peak hours, and sentiment. |
| analyze_sentimentB | Run sentiment analysis on posts. Provide a query to search timeline data, or pass texts directly. Returns positive/negative/neutral breakdown. |
| compareB | Compare 2+ profiles, hashtags, or topics side-by-side across engagement, sentiment, and volume metrics. |
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 14 tools
Most tools have distinct purposes, with clear separation between scraping (platform-specific), analysis (profile, sentiment, comparison), and timeline operations (query, search, stats, trends). However, timeline_query and timeline_search could be confused as both search the timeline database, though one is structured and the other semantic.
Tool names follow a consistent snake_case pattern throughout, with clear verb_noun structures (e.g., analyze_profile, scrape_facebook, timeline_query). The naming is predictable and readable, with no mixing of conventions or styles.
14 tools is well-scoped for a social research server covering multiple platforms and analysis types. Each tool earns its place, providing comprehensive coverage without being overwhelming, typical for a domain with diverse data sources and analytical needs.
The toolset offers complete coverage for social research: scraping from major platforms (Facebook, Instagram, etc.), storing data in a timeline database, and providing analysis tools (profile analysis, sentiment, comparison, stats, trends). No obvious gaps exist for the stated purpose, enabling agents to perform end-to-end research workflows.