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rampify-dev

Rampify MCP Server

by rampify-dev

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
API_KEYYesYour API key from Rampify dashboard (starts with sk_live_...)
CACHE_TTLNoCache duration in seconds3600
LOG_LEVELNoLogging level: debug, info, warn, or errorinfo
BACKEND_API_URLNoRampify API endpoint - always use https://www.rampify.devhttps://www.rampify.dev
SEO_CLIENT_DOMAINNoDefault domain for this project (e.g., yoursite.com or localhost:3000)

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_page_seo

Get comprehensive SEO data and insights for a specific page. Returns performance metrics from Google Search Console, detected issues, optimization opportunities, and actionable recommendations.

get_issues

Get SEO issues for entire site with health score. Returns health score (0-100), categorized issues by severity, and prioritized recommendations for fixes.

crawl_site

Trigger a fresh site crawl and analysis. Use this after deploying changes to refresh SEO data. Crawls the entire site, checks all URLs, detects issues, and updates the database with current SEO status.

generate_schema

Auto-generate structured data (schema.org JSON-LD) for any page. Detects page type (Article, Product, FAQ, etc.) and generates appropriate schema with validation. Returns ready-to-use code snippets.

generate_meta

Generate optimized meta tags (title, description, OG tags) for a page. Analyzes page content and provides recommendations for SEO-optimized meta tags based on actual content, headings, and topics.

get_gsc_insights

Get Google Search Console performance insights with AI-powered content recommendations. Returns top performing pages, query opportunities (improve CTR, rankings, keyword gaps), and actionable recommendations for what content to write next.

create_feature_spec

Create and save a feature specification to Rampify.

IMPORTANT: Before calling this tool, YOU (Claude) must generate the complete structured spec from the user's description and your codebase context. Do not pass raw natural language — populate all fields:

  • Infer affected_files from open files and the codebase structure

  • Infer tech_stack from package.json and imports

  • Generate 3-5 acceptance criteria covering happy path, edge cases, and error handling

  • Break implementation into 3-8 concrete tasks with file references

  • Write ai_context_summary to help future AI agents understand the approach

  • Set next_action to the single most important first step

get_feature_spec

Retrieve a feature specification from Rampify. Use this when starting work on a feature to understand what to build, which files to touch, and what the acceptance criteria are.

Two lookup modes:

  • spec_id: fetch a specific spec with full criteria and tasks (use this when you know the ID)

  • search: keyword search across titles and descriptions (returns a list; follow up with spec_id for full details)

update_feature_spec

Update a feature spec to reflect actual progress. Mark tasks and criteria as complete, update spec status, and advance next_action.

Use this after completing work described in a spec task. Returns a suggested_commit message string.

Examples:

  • Mark a task complete: { spec_id, task_id, task_status: "completed" }

  • Update overall status: { spec_id, status: "in_progress" }

  • Mark a criterion verified: { spec_id, criterion_id, criterion_status: "verified" }

get_security_context

Get security analysis for a site (homepage scan only). Returns security score, detected issues (headers, SSL, exposed files, third-party scripts), and actionable remediation steps. PRIVATE BETA.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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