About Social Neuron
Social Neuron is an MCP server and CLI for social media content management, aimed at teams and agents that plan, create, publish, and measure content. Its tools span trend research through performance feedback, including scheduling and approval workflows.
Key features
- 01Research trends and generate content ideas
- 02Create videos, images, voiceovers, and carousels
- 03Schedule and publish across platforms
- 04Track analytics and performance insights
- 05Manage brands, comments, and content plans
- 06Configure autopilot and quality checks
Use cases
- 01Plan and produce a weekly content batch
- 02Schedule content across social platforms
- 03Review performance and adjust future plans
- 04Approve content plans and manage comments
MCP support
It exposes tools for social content creation, scheduling and distribution, analytics, comment management, and automated scheduling to MCP clients. The hosted HTTP service also provides Content Calendar and Analytics Pulse MCP Apps.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y @socialneuron/mcp-serverSOCIALNEURON_API_KEYSecretYour Social Neuron API key. Generate at https://socialneuron.com/settings/developerLocal servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README@socialneuron/mcp-server
91 public MCP tools for AI-powered social media management. Create content, schedule posts, track analytics, and optimize performance — all from Claude Code or any MCP client.
Quick Start
1. Authenticate
npx -y @socialneuron/mcp-server login --device
This opens your browser to authorize access. Requires a Social Neuron Pro plan or higher. See pricing.
2. Add to Claude Code
claude mcp add socialneuron -- npx -y @socialneuron/mcp-server
Claude Desktop
Add to your claude_desktop_config.json:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"socialneuron": {
"command": "npx",
"args": ["-y", "@socialneuron/mcp-server"]
}
}
}
VS Code
Add to .vscode/mcp.json in your workspace:
{
"servers": {
"socialneuron": {
"command": "npx",
"args": ["-y", "@socialneuron/mcp-server"]
}
}
}
Cursor
Add to .cursor/mcp.json in your workspace:
{
"mcpServers": {
"socialneuron": {
"command": "npx",
"args": ["-y", "@socialneuron/mcp-server"]
}
}
}
3. Start using
Ask Claude: "What content should I post this week?" or "Schedule my latest video to YouTube and TikTok"
What You Can Do
Ask Claude things like:
- "Generate 5 content ideas about sustainable fashion for Gen Z"
- "Create a 30-second video ad for my product launch"
- "Schedule this post to X and Bluesky at 9am tomorrow"
- "Show me my best-performing content this month"
- "What are the trending topics in my niche right now?"
- "Check my analytics and suggest improvements"
- "Set up autopilot to post 3 times per week"
Tool Categories
The npm package exposes 91 public tools per transport. The separately versioned hosted service exposes 92 public tools, including hosted-only get_account_status. Hosted HTTP includes the Content Calendar and Analytics Pulse MCP Apps; npm stdio includes 2 local screen-capture tools instead. The live hosted count is published by the server card. The npm package supports Node 20.20+ and Node 22.22+ under its declared engine ranges. The hosted service runs its separate 3.0.0 contract; its version is recorded alongside its reviewed tool inventory in server.json.hosted.
These tools are available to AI agents (Claude, Cursor, etc.) via the MCP protocol.
Content Lifecycle
| Category | Tools | What It Does |
|---|---|---|
| Ideation | generate_content, fetch_trends, adapt_content, get_ideation_context | AI-powered content ideas and trend research |
| Content | generate_video, generate_image, generate_voiceover, generate_carousel, check_status, create_storyboard | Video, image, voiceover, and carousel creation with 20+ AI models |
| Distribution | schedule_post, reschedule_post, schedule_content_plan, find_next_slots, list_connected_accounts, list_recent_posts | Project-scoped multi-platform publishing, scheduling, rescheduling, and slot optimization |
| Analytics | fetch_analytics, refresh_platform_analytics | Performance tracking across all platforms |
| Insights | get_performance_insights, get_best_posting_times | Data-driven content optimization |
Management & Optimization
| Category | Tools | What It Does |
|---|---|---|
| Brand | extract_brand, get_brand_profile, save_brand_profile, update_platform_voice | Brand identity and voice management |
| Comments | list_comments, reply_to_comment, post_comment, moderate_comment, delete_comment | Social engagement management |
| Lifecycle | cancel_async_job, cancel_scheduled_post, delete_carousel, delete_content_plan, delete_autopilot_config | Confirmed, project-scoped cancellation and cleanup with explicit refund status |
| Planning | plan_content_week, save_content_plan, get_content_plan, update_content_plan, submit_content_plan_for_approval | Content calendar and approval workflows |
| Plan Approvals | create_plan_approvals, respond_plan_approval, list_plan_approvals | Review and approve content plans |
| Autopilot | list_autopilot_configs, get_autopilot_status, update_autopilot_config | Automated content scheduling |
| Quality | quality_check, quality_check_plan | Pre-publish content validation |
| Credits | get_credit_balance, get_budget_status | Usage and budget tracking |
| Loop | get_loop_summary | Closed-loop optimization feedback |
Utilities
| Category | Tools | What It Does |
|---|---|---|
| Extraction | extract_url_content | Extract content from URLs, YouTube, articles |
| Screenshots | capture_app_page, capture_screenshot | Visual documentation and monitoring |
| Remotion | list_compositions, render_demo_video | Programmatic video rendering |
| Usage | get_mcp_usage | API usage monitoring |
| YouTube | fetch_youtube_analytics | YouTube-specific deep analytics |
| Discovery | search_tools | Find tools by keyword with progressive detail levels (saves 98% tokens vs loading all tools) |
Interactive MCP Apps (hosted HTTP)
| App | Open tool | Purpose |
|---|---|---|
| Content Calendar | open_content_calendar | Project-scoped calendar, quick create, and drag-to-reschedule |
| Analytics Pulse | open_analytics_pulse | Project-scoped KPI, platform-mix, and top-post performance dashboard |
Apps render only in MCP hosts that support the MCP Apps extension. All underlying data and write operations remain ordinary scoped tools, so hosts without interactive UI can use the same workflows through text/tool calls.
Authentication
Three auth methods, in order of recommendation:
Device Code (Recommended)
npx -y @socialneuron/mcp-server login --device
Opens browser, you approve, CLI receives API key automatically.
Browser Flow
npx -y @socialneuron/mcp-server login
Browser-based OAuth flow.
API Key Paste
npx -y @socialneuron/mcp-server login --paste
Generate a key at socialneuron.com/settings/developer, paste it in.
Keys are stored in your OS keychain (macOS Keychain, Linux secret-tool) or a file fallback created with owner-only permissions where the operating system supports them.
Windows users: The file fallback (
~/.config/social-neuron/credentials.json) does not have strong permission enforcement on NTFS. For production use on Windows, set theSOCIALNEURON_API_KEYenvironment variable instead.
Pricing
MCP/API access requires a Pro plan or higher:
| Plan | Price | Credits/mo | MCP/API Access |
|---|---|---|---|
| Free | $0 | 50 | — |
| Starter | $19/mo | 500 | — |
| Pro | $49/mo | 1,500 | MCP/API: Read + Analytics + Write + Distribute |
| Team | $99/mo | 3,500 | Full MCP/API + 5 keys |
| Agency | $249/mo | 10,000 | Full MCP/API + 20 keys |
Sign up at socialneuron.com/pricing.
Scopes
Each API key inherits scopes from your plan. Tools require specific scopes to execute.
| Scope | What you can do |
|---|---|
mcp:read | Analytics, insights, brand profiles, content plans, quality checks, screenshots, usage stats, credit balance |
mcp:write | Generate content (video, image, voiceover, carousel), create storyboards, save brand profiles, plan content |
mcp:distribute | Schedule posts, publish content plans |
mcp:analytics | Refresh analytics, YouTube deep analytics |
mcp:comments | List, reply, post, moderate, delete comments |
mcp:autopilot | Configure and monitor automated scheduling |
mcp:full | All of the above |
CLI Reference
These commands run directly in your terminal — no AI agent needed. Useful for scripts, CI/CD, and quick checks.
After global install (
npm i -g @socialneuron/mcp-server), usesocialneuron-mcpdirectly. Otherwise, prefix withnpx @socialneuron/mcp-server.
# Auth
socialneuron-mcp login [--device|--paste]
socialneuron-mcp logout
# Deterministic CLI (no LLM)
socialneuron-mcp sn publish --media-url <url> --caption <text> --platforms <list> --confirm
socialneuron-mcp sn status --job-id <id>
socialneuron-mcp sn posts --days 7 --platform youtube
socialneuron-mcp sn refresh-analytics
socialneuron-mcp sn preflight --check-urls
socialneuron-mcp sn oauth-health --json
socialneuron-mcp sn oauth-refresh --platform instagram
socialneuron-mcp sn quality-check --content "your text here"
socialneuron-mcp sn autopilot
socialneuron-mcp sn usage
socialneuron-mcp sn loop
socialneuron-mcp sn credits
# Agent-native CLI v2
socialneuron-mcp sn tools [--module ideation] [--scope mcp:write] # List/filter available tools
socialneuron-mcp sn info # Version, auth, credits, tool count
socialneuron-mcp sn plan list|view|approve # Content plan management
socialneuron-mcp sn preset list|show|save|delete # Platform presets (6 built-in)
# Interactive REPL
socialneuron-mcp repl
# Add --json to any command for machine-readable output
Automation Flow (E2E Loop)
The full autonomous content loop using MCP tools:
get_loop_summary— assess project state (content count, scheduled posts, insights)plan_content_week— generate a content plan based on insights and trendsgenerate_video/generate_image— create media assets from the plancheck_status— poll async jobs until assets are readyschedule_post— distribute content to connected platforms- (wait for analytics collection) — platform data is fetched automatically
refresh_platform_analytics— trigger a manual analytics refreshget_performance_insights— read what worked and what didn't- Loop back to step 1 with new insights
Each iteration produces smarter content as performance data feeds back into the planning step.
Security
- All API keys are hashed before storage — we never store plaintext keys
- Credentials stored in your OS keychain (macOS Keychain, Linux secret-tool) or environment variable
- SSRF protection on all URL parameters with DNS rebinding prevention
- Rate limiting per user with per-tool limits for expensive operations
- Agent loop detection prevents runaway automation
- Set
DO_NOT_TRACK=1to disable anonymous usage telemetry
See SECURITY.md for our vulnerability disclosure policy and credential safety details.
Telemetry
This package collects operational usage metrics (tool name, duration, success/failure) to improve reliability. It does not send tool inputs, outputs, generated content, API keys, emails, or upstream error bodies. When a deployment configures POSTHOG_PSEUDONYMIZATION_KEY, the user identifier is HMAC-pseudonymized; otherwise an ephemeral per-process key prevents stable cross-session correlation.
To disable: Set DO_NOT_TRACK=1 or SOCIALNEURON_NO_TELEMETRY=1 in your environment.
No personal content, API keys, or request payloads are ever collected.
Examples
See the examples repo for prompt-driven workflow templates:
- Weekly content batch planning
- Cross-platform content repurposing
- Performance review and optimization loops
- Brand-aligned content generation
- Comment engagement automation
Links
License
MIT - see LICENSE
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.