Glindr Native MCP Documentation

Overview

Glindr Native MCP is the SSNATW AI mcp for Glindr. It gives the platform a dedicated runtime for visibility optimization and reach analysis, so the experience feels native, fast, and fully integrated with the rest of the product.

The mcp follows the same marketplace installation and agent attachment model used across SSNATW. After activation, it can run under standard permissions or under ranks that include root access, which can manage the full mcp lifecycle, credentials, recovery actions, and advanced controls.

This guide documents the mcp as a live product capability. It covers what the mcp does, what users can expect to see, which service endpoints support it, and how the core runtime objects are structured.

Capabilities

Glindr Native MCP is designed as a first-class AI mcp. The workflow below describes how the runtime, user experience, and management layer fit together in production.

1. Install the mcp and assign it to the correct dating profile agent.
2. Activate AI visibility strategy and conversation prioritization policies.
3. Track profile movement through the core dating metrics shown to the user.

API Surface

The mcp surface is split into marketplace APIs for discovery and installation, runtime APIs for AI execution and analytics, and management APIs for configuration and advanced control.

Function Calls and Integration Examples

The following snippets show the mcp from a real integration perspective: install it, read its attached state, then drive runtime behavior and analytics through explicit service calls.

import { installMarketplaceMcp } from '../api/marketplace';

await installMarketplaceMcp({
  offerId: <mcp-id>,
  agentUuid: '<agent-uuid>',
  installMode: 'purchase',
  notes: 'Enable Glindr Native MCP on the primary Glindr agent.'
});

import { listAgentMcps } from '../api/agents';

const attachments = await listAgentMcps(<agent-id>);
const installed = attachments.find((item) => item.offer_slug === 'native-glindr');

if (installed?.status === 'active') {
  console.log('Glindr Native MCP is live on this agent');
}

import { apiFetch } from '../api/client';

await apiFetch('/api/mcp/native-glindr/runtime/execute', {
  method: 'POST',
  body: JSON.stringify({
    agent_uuid: '<agent-uuid>',
    intent: 'optimize_visibility',
    context: {
      platform: 'glindr',
      priority: 'high',
      campaign: 'spring-launch'
    }
  })
});

const insights = await apiFetch('/api/mcp/native-glindr/runtime/insights');
console.log(insights.summary);

MCP Data Structures

These structures define the core mcp object, the installed attachment record, and the runtime data shape used by the AI orchestration and analytics layers.

export interface MarketplaceMcpRecord {
  id: number;
  slug: 'native-glindr';
  name: 'Glindr Native MCP';
  version: string;
  status: 'active' | 'published' | 'beta' | 'deprecated';
  description: string;
  author?: string | null;
  mcp_type: 'social';
  platform: 'glindr';
  capabilities: string[];
  required_permissions: string[];
  documentation_url?: string | null;
  pricing_model?: 'free' | 'one_time' | 'subscription' | 'revenue_share';
  price?: number | null;
  revenue_share_percent?: number | null;
  is_official?: boolean;
  install_count?: number;
  rating?: number;
  review_count?: number;
  created_at?: string;
  updated_at?: string;
}

export interface AgentMcpAttachment {
  id: number;
  agent_id: number;
  offer_id: number;
  offer_name: string;
  offer_slug: string;
  status: string;
  install_mode: 'trial' | 'purchase' | 'queued';
  billing_model: string;
  revenue_share_percent?: number | null;
  upfront_price?: number | null;
  notes?: string | null;
  created_at: string;
  activated_at?: string | null;
}

export interface McpRuntimeInsight {
  mcp_slug: 'native-glindr';
  platform: 'glindr';
  agent_uuid: string;
  status: 'active' | 'degraded' | 'paused';
  summary: string;
  metrics: {
      visible_score_percent: 67,
      accounts_reached: 412
  };
  controls: {
    automation_mode: 'assisted' | 'autonomous' | 'priority';
    access_tier: 'standard' | 'root';
  };
  updated_at: string;
}

MCP Lifecycle

1. Discover the mcp in the marketplace and open its detail page.
2. Install it to the target private agent or shared agent through the marketplace installation flow.
3. Activate the runtime profile, channel policy, and AI behavior rules that define how the mcp should operate.
4. Allow the mcp to execute publishing, messaging, visibility, or monetization tasks through the AI runtime layer.
5. Review health, insights, and control status through the mcp management surface.
6. Scale, refine, or override behavior as needed through standard controls or rank-based root access.

Platform Notes

• Glindr should remain the canonical platform identifier across routing, analytics, caching, and UI state.
• Dating mcps should stay intentionally narrow on the dashboard and continue to center Visible score % and Accounts reached.
• Configuration, credentials, and advanced controls should stay consistent across marketplace, runtime, and management surfaces.
• Ranks that include root access are allowed to manage installation, runtime policy, credentials, execution controls, analytics settings, and recovery actions across the full mcp surface.
• MCP schemas should stay additive and versionable so the runtime can evolve without breaking existing agents or dashboards.

Frequently Asked Questions