Server definition
- Hash
- sha256:a66da95fb4edab528f700561061b570c86ba5c6c8a4ab5ef084848d7afc98499
- What it is
- What a remote MCP server returned when asked what it offers: 13 tools
The blob, as servednamed by its sha256
{
"instructions": "You have access to COS (Content Optimization System) -\n a professional communication analysis platform. Use these tools to analyze\n content for engagement, personality fit, strategic clarity, and cognitive framing.\n\n Core 4 frameworks:\n - Engagement Analysis: Emotional engagement scoring (impact, novelty, relevance)\n - Personality Analysis: Personality-based communication (OCEAN model)\n - Strategic Clarity: Business message alignment (value prop, differentiation, CTA)\n - Framing Strategy: Cognitive frames and power positioning\n\n Extended 3 frameworks:\n - Persuasion Analysis: Domain-specific (business, politics, health, masculinity, comedy)\n - Platform Analysis: Platform-specific optimization (13 platforms)\n - Quality Analysis: 5-dimension quality assessment\n\n Best practices:\n - Use analyze_content for core 4-framework analysis\n - Use analyze_full_comms for comprehensive 7-framework analysis\n - Use analyze_persuasion/platform/quality for targeted extended analysis\n - Check get_templates for pre-built analysis scenarios\n - Always specify platform and target_audience for best results\n ",
"tools": [
{
"description": "Analyze content using all 4 COS frameworks in parallel.\n\nReturns comprehensive analysis with:\n- Overall scores (0-10) for each framework\n- Dimension breakdowns with weights\n- Specific recommendations for improvement\n- Cross-framework insights",
"inputSchema": {
"additionalProperties": false,
"properties": {
"content": {
"description": "The text content to analyze (min 50 characters)",
"type": "string"
},
"platform": {
"default": "general",
"description": "Target platform for optimization (affects scoring weights)",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"target_audience": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Description of intended audience (improves relevance scoring)"
}
},
"required": [
"content"
],
"type": "object"
},
"name": "analyze_content",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Analyze content using a single specific framework.\n\nFaster than full analysis when you only need one perspective.\n\nFrameworks:\n- hape: Engagement Analysis (novelty, relevance, emotional valence)\n- big_five: Personality Analysis using OCEAN model (openness, conscientiousness, extraversion, agreeableness, neuroticism)\n- strategic_clarity: Business message clarity (value prop, differentiation, CTA)\n- framing_strategy: Cognitive frames and power positioning",
"inputSchema": {
"additionalProperties": false,
"properties": {
"content": {
"description": "The text content to analyze (min 50 characters)",
"type": "string"
},
"framework": {
"description": "Which analysis framework to use",
"enum": [
"hape",
"big_five",
"strategic_clarity",
"framing_strategy"
],
"type": "string"
},
"platform": {
"default": "general",
"description": "Target platform for optimization",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"target_audience": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Description of intended audience"
},
"temperature": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"description": "Optional LLM sampling temperature. Pass 0.0 for deterministic\nscoring (validation harnesses, classification-agreement gates). Leave\nunset (None) for the backend default. Forwarded to the analyze\nendpoint, which has accepted this parameter since cos-bbf."
}
},
"required": [
"content",
"framework"
],
"type": "object"
},
"name": "analyze_framework",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Run all 7 COS frameworks in parallel for comprehensive analysis.\n\nThis is the most thorough analysis option, running:\n- Core 4: HAPE, Big Five, Strategic Clarity, Sovereign Mind\n- Extended 3: Persuasion (domain-specific), Platform, Quality\n\nUse this when you need complete analysis across all dimensions.\nTakes longer but provides the most comprehensive view.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"content": {
"description": "The text content to analyze (min 50 characters)",
"type": "string"
},
"domain": {
"default": "business",
"description": "Domain for persuasion analysis",
"enum": [
"business",
"politics",
"health",
"masculinity",
"comedy"
],
"type": "string"
},
"platform": {
"default": "linkedin",
"description": "Target platform for optimization",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"target_audience": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Description of intended audience"
}
},
"required": [
"content"
],
"type": "object"
},
"name": "analyze_full_comms",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Analyze content using domain-specific persuasion frameworks.\n\nEach domain has specialized scoring dimensions:\n- business: B2B/B2C messaging, ROI framing, objection handling\n- politics: Political messaging, polarization awareness, coalition building\n- health: Medical accuracy, safety messaging, behavior change (CRITICAL domain)\n- masculinity: Identity messaging, status signaling, tribe alignment\n- comedy: Humor mechanics, timing, callback patterns",
"inputSchema": {
"additionalProperties": false,
"properties": {
"content": {
"description": "The text content to analyze (min 50 characters)",
"type": "string"
},
"domain": {
"default": "business",
"description": "The domain context for persuasion analysis",
"enum": [
"business",
"politics",
"health",
"masculinity",
"comedy"
],
"type": "string"
},
"platform": {
"default": "general",
"description": "Target platform for optimization",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"target_audience": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Description of intended audience"
},
"temperature": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"description": "Optional LLM sampling temperature. Pass 0.0 for deterministic\nscoring (validation harnesses, classification-agreement gates). Leave\nunset (None) for the backend default. Forwarded to the persuasion\nendpoint, which has accepted this parameter since cos-bbf."
}
},
"required": [
"content"
],
"type": "object"
},
"name": "analyze_persuasion",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Analyze content for platform-specific optimization.\n\nEvaluates content against platform constraints and algorithm preferences:\n- Character limits and formatting rules\n- Algorithm optimization signals\n- Engagement pattern recommendations\n- Platform-specific best practices\n\nSupported platforms: twitter, linkedin, email, youtube, tiktok, instagram,\nfacebook, medium, substack, podcast, newsletter, slack, discord",
"inputSchema": {
"additionalProperties": false,
"properties": {
"content": {
"description": "The text content to analyze (min 50 characters)",
"type": "string"
},
"platform": {
"default": "linkedin",
"description": "The target platform for optimization",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"target_audience": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Description of intended audience"
}
},
"required": [
"content"
],
"type": "object"
},
"name": "analyze_platform",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Analyze content quality across 5 dimensions.\n\nQuality dimensions evaluated:\n- Clarity: Is the message easy to understand?\n- Coherence: Does the content flow logically?\n- Correctness: Grammar, spelling, factual accuracy\n- Completeness: Are all necessary elements present?\n- Conciseness: Is the content appropriately tight?",
"inputSchema": {
"additionalProperties": false,
"properties": {
"content": {
"description": "The text content to analyze (min 50 characters)",
"type": "string"
},
"platform": {
"default": "general",
"description": "Target platform context",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"target_audience": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Description of intended audience"
}
},
"required": [
"content"
],
"type": "object"
},
"name": "analyze_quality",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Infer OCEAN personality profile from an audience description.\n\nMaps a free-text target audience description into a structured psychological\nprofile suitable for personalized outreach (cold email, ads, sales messaging).\n\nReturns:\n- OCEAN scores (openness, conscientiousness, extraversion, agreeableness, neuroticism)\n- ocean_confidence (0.0-1.0) — low when signals are weak\n- elm_route (\"central\" | \"peripheral\" | \"mixed\") — how the audience processes persuasion\n- dominant_traits + trait_rationale\n- dominant_moral_foundations (Moral Foundations Theory)\n- vulnerability_flags — audiences requiring careful ethics review\n- recommended_persuasion_principle (Cialdini) + persuasion_rationale\n\nCommon use: feed a CRM Person/Account description (title, industry, recent\nsignals) to get a psychology-grounded targeting profile for that prospect.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"audience_description": {
"description": "Free-text description of the target audience (10-2000 chars).\nInclude role, industry, behaviors, pain points, recent signals.",
"type": "string"
},
"campaign_objective": {
"default": "conversion",
"description": "Campaign goal (e.g. \"awareness\", \"conversion\", \"retention\",\n\"cold_outreach\").",
"type": "string"
},
"domain": {
"default": "business",
"description": "Campaign domain context (e.g. \"B2B\", \"ecommerce\", \"health\", \"financial\").",
"type": "string"
}
},
"required": [
"audience_description"
],
"type": "object"
},
"name": "audience_profile",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Have a conversation with the COS analysis agent.\n\nThe agent can help you:\n- Analyze content interactively\n- Get recommendations for improvement\n- Understand framework scores\n- Configure analysis settings",
"inputSchema": {
"additionalProperties": false,
"properties": {
"conversation_id": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Optional ID to continue an existing conversation"
},
"message": {
"description": "Your message to the COS agent",
"type": "string"
}
},
"required": [
"message"
],
"type": "object"
},
"name": "chat",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Execute a specific template with provided variables.\n\nTemplates guide the analysis with pre-defined prompts and variable placeholders.\nFirst use get_templates to find available templates and their required variables.",
"inputSchema": {
"additionalProperties": false,
"properties": {
"platform": {
"default": "general",
"description": "Target platform for optimization",
"enum": [
"twitter",
"linkedin",
"email",
"youtube",
"tiktok",
"instagram",
"facebook",
"medium",
"substack",
"podcast",
"newsletter",
"slack",
"discord",
"general"
],
"type": "string"
},
"template_id": {
"description": "The template ID to execute (from get_templates)",
"type": "string"
},
"variables": {
"additionalProperties": true,
"description": "Dictionary of variable values required by the template",
"type": "object"
}
},
"required": [
"template_id",
"variables"
],
"type": "object"
},
"name": "execute_template",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Get detailed information about a specific template.\n\nReturns the template's:\n- Name and description\n- Required and optional variables with types\n- Categories and tags\n- Scoring dimensions and weights",
"inputSchema": {
"additionalProperties": false,
"properties": {
"template_id": {
"description": "The template ID to get details for",
"type": "string"
}
},
"required": [
"template_id"
],
"type": "object"
},
"name": "get_template_details",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "List available analysis templates.\n\nTemplates are pre-configured analysis scenarios for common use cases:\n- Email outreach optimization\n- LinkedIn post analysis\n- Sales pitch review\n- Content marketing assessment",
"inputSchema": {
"additionalProperties": false,
"properties": {
"category": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Filter by template category (e.g., \"email\", \"social\", \"sales\")"
},
"search": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Search templates by name or description"
}
},
"type": "object"
},
"name": "get_templates",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Generate or refine a personalized cold email for a CRM prospect.\n\nComposite tool: combines audience profiling (OCEAN + Cialdini),\noptional agent profiling from writing samples, draft generation\n(if no draft is supplied), and persuasion + platform scoring in\na single call. Designed for CRM integrations like Clarify, HubSpot,\nSalesforce — pass a Person/Account context, get back a draft + scoring.\n\nReturns:\n- audience_profile: OCEAN scores, ELM route, Cialdini principle\n- agent_profile: prospect's writing style (if samples provided)\n- draft: generated or echoed email body\n- draft_was_generated: bool — whether COS generated the draft\n- persuasion + platform: full scoring breakdowns\n- rewrites: prioritized rewrite suggestions\n- one_thing: the single most important next step\n- cialdini_principle: recommended influence principle",
"inputSchema": {
"additionalProperties": false,
"properties": {
"audience_description": {
"description": "REQUIRED. Free-text describing the prospect\n(role, industry, behaviors, pain points, recent signals).\n10-2000 chars. This seeds the audience profile.",
"type": "string"
},
"company": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"domain": {
"default": "business",
"description": "Persuasion domain (default \"business\").",
"type": "string"
},
"draft": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Existing draft to score + refine. If None, a draft is generated."
},
"include_scoring": {
"anyOf": [
{
"type": "boolean"
},
{
"type": "null"
}
],
"default": null,
"description": "Run persuasion + platform scoring on the draft.\nDefault (None): scoring runs ONLY when a draft was supplied (refine path).\nOn the generate path scoring is skipped by default (cuts latency from\n~45s to ~10s). Set True to force scoring on a generated draft, or\nFalse to suppress scoring even when refining."
},
"industry": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"intent": {
"default": "cold_outreach",
"description": "Email intent (\"cold_outreach\", \"follow_up\", \"reactivation\",\n\"warm_intro\", \"demo_request\", \"discovery_call\", \"proposal_recap\").",
"enum": [
"cold_outreach",
"follow_up",
"reactivation",
"warm_intro",
"demo_request",
"discovery_call",
"proposal_recap"
],
"type": "string"
},
"name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"recent_signals": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "List of recent activity/triggers from the CRM\n(e.g. [\"downloaded ROI calculator\", \"viewed pricing 3x\"])."
},
"sender_context": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"description": "Who the sender is and what they're pitching."
},
"title": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null
},
"writing_samples": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"description": "0-5 prospect writing samples (emails, posts).\nEach ≥50 chars. Profiled if provided."
}
},
"required": [
"audience_description"
],
"type": "object"
},
"name": "optimize_email_for_prospect",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
},
{
"description": "Profile an agent's personality from their writing samples.\n\nAnalyzes 1-10 writing samples (3-5 recommended) to infer the author's\nBig Five (OCEAN) personality traits, communication style, strengths,\nblind spots, and persuasion profile.\n\nThis is the inverse of content analysis — instead of \"is this content effective?\",\nit answers \"who is this writer based on how they communicate?\"",
"inputSchema": {
"additionalProperties": false,
"properties": {
"agent_name": {
"default": "Unknown Agent",
"description": "Name of the agent being profiled",
"type": "string"
},
"samples": {
"description": "List of writing samples from the agent (min 50 chars each, 3-5 recommended)",
"items": {
"type": "string"
},
"type": "array"
}
},
"required": [
"samples"
],
"type": "object"
},
"name": "profile_agent",
"outputSchema": {
"additionalProperties": true,
"type": "object"
}
}
]
}Verify it yourself
curl -s https://api.teppi.xyz/v1/evidence/sha256:a66da95fb4edab528f700561061b570c86ba5c6c8a4ab5ef084848d7afc98499 | sha256sum