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Pinterest Ads MCP Server

  • 4 repo stars
  • Updated July 27, 2026
  • cesteral/mcp-open-advertising

Pinterest Ads MCP Server is a MCP server that manages Pinterest advertising with CRUD, async reports, targeting, and audience estimates.

About

Pinterest Ads MCP Server connects Pinterest’s advertising APIs to Model Context Protocol clients so developers can manage visual discovery campaigns from an AI agent. It suits founders in ecommerce, content, or lifestyle SaaS who rely on Pinterest for top-of-funnel traffic and want to adjust targeting, budgets, and creative sets without constant dashboard context switching. Capabilities include standard CRUD operations, asynchronous reporting for metrics-heavy pulls, targeting helpers, and audience size estimates to sanity-check reach before launching. Deploy locally through npm stdio or host the remote URL pattern documented in server.json. You need Pinterest Ads API access and comfort with intermediate API-backed tooling; it does not replace Pinterest’s policy review or creative strategy skills.

  • Pinterest Ads CRUD for campaigns and related entities via MCP
  • Async reports for pin and campaign performance
  • Targeting configuration tools exposed to the agent
  • Audience estimate calls before spend commitments
  • stdio @cesteral/pinterest-mcp v1.1.0 and optional deployed streamable-http endpoint

Pinterest Ads MCP Server by the numbers

  • Data as of Jul 28, 2026 (Skillselion catalog sync)
terminal
claude mcp add pinterest-mcp -- npx -y @cesteral/pinterest-mcp

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repo stars4
Package@cesteral/pinterest-mcp
TransportSTDIO, HTTP
AuthNone
Last updatedJuly 27, 2026
Repositorycesteral/mcp-open-advertising

What it does

Run Pinterest Ads campaigns, targeting, and audience estimates through your agent when promoting visual products or content.

Who is it for?

Visual-first brands and shop owners running Pinterest Ads who want programmatic campaign control via MCP.

Skip if: Products with no Pinterest ad account or teams that only need organic pin scheduling without paid tools.

What you get

You can iterate Pinterest ad structure and pull report jobs from the same agent thread that handles your product work.

  • Updated Pinterest ad campaigns and targeting settings
  • Audience estimate outputs for planning reach
  • Async report data for optimization decisions

By the numbers

  • Server version 1.1.0
  • npm identifier @cesteral/pinterest-mcp
  • Remote path /pinterest-mcp/mcp on configurable host
README.md

Cesteral MCP Servers

Self-hostable MCP connectors for major advertising platforms.

Use this repo when you want transparent platform integrations, local experimentation, and infrastructure you control. Use Cesteral Intelligence when your team needs approvals before spend commits, credential brokering, auditability, and cross-platform execution from one governed environment.

Try Meta Ads MCP locally (~10 min) | Compare OSS vs Cesteral Intelligence | Book a workflow demo

License TypeScript MCP

DV360   Google Ads   The Trade Desk   Meta   LinkedIn   TikTok   CM360   SA360   Pinterest   Snapchat   Amazon DSP   Microsoft Ads


Two Ways to Use This

This repo is an open connector layer, not the full product.

  • Self-host a connector for transparency and direct control of your credentials, infrastructure, and platform access.
  • Use Cesteral Intelligence when the workflow needs governed writes, team approvals, credential brokering, auditability, and cross-platform coordination — see when you need it below.

Flagship Connectors

Google Ads Google Ads MCP

Campaign writes, GAQL reporting, bid adjustments, previews, and validation via Google Ads REST API v23.

Package docs | Use with Cesteral Intelligence

Meta Meta Ads MCP

Campaign writes, insights, targeting discovery, delivery estimates, previews, and bulk operations via Meta Marketing API v25.0.

Package docs | Use with Cesteral Intelligence

DV360 DV360 MCP

Campaign writes, targeting, custom bidding, previews, uploads, and schema-driven validation via DV360 API v4.

Package docs | Use with Cesteral Intelligence


When You Need Cesteral Intelligence

The OSS connectors give you per-server tool execution + audit logs. Cesteral Intelligence layers governance and orchestration on top:

  • Credential brokering -- keep platform secrets out of local operator workflows
  • Approval workflows -- require human review before destructive or high-spend changes
  • Aggregated audit -- unified, cross-server activity feed with provenance, tied to operator identity
  • Cross-platform orchestration -- coordinate governed execution across multiple connectors
  • Team operations -- shared workflows, tenant isolation, and operator visibility

Compare OSS connectors vs Cesteral Intelligence


The Full Fleet

Server Platform Tools Auth
gads-mcp Google Ads REST API v23 15 OAuth2 refresh token
meta-mcp Meta Marketing API v25.0 27 Bearer token
dv360-mcp DV360 API v4 26 Google OAuth2 / service account
ttd-mcp The Trade Desk REST + GraphQL API 43 User token (TTD-Auth header)
linkedin-mcp LinkedIn Marketing API v2 21 Bearer token
tiktok-mcp TikTok Marketing API v1.3 24 Bearer token + advertiser ID
cm360-mcp CM360 API v5 21 Google OAuth2
sa360-mcp SA360 Reporting API v0 + DS v2 16 OAuth2 refresh token
pinterest-mcp Pinterest Ads API v5 23 Bearer token
snapchat-mcp Snapchat Ads API v1 23 Bearer token
amazon-dsp-mcp Amazon DSP API 26 Bearer token
msads-mcp Microsoft Advertising API v13 25 Access token + developer token
dbm-mcp Bid Manager API v2 6 Google OAuth2

Thirteen servers, 290+ tools. Tool counts are the live registered total per server, including the *_search_tools discovery tool where present.

What Every Server Ships

These connectors have grown past "thin REST wrappers." Beyond raw tool calls, every server in the fleet exposes the full surface of the modern MCP spec (protocol revisions 2025-03-26 through 2025-11-25):

  • MCP Prompts — on-demand, multi-step workflow guidance (campaign launch, reporting, troubleshooting) so agents don't have to rediscover each platform's sequencing. Present on all 13 servers.
  • MCP Resources — structured, addressable context (schemas, field catalogs, examples, enums) fetched on demand instead of bloating every tool schema. Present on all 13 servers. DV360 uses these to keep its >1 MB discriminated unions off the wire (entity-schema://, entity-fields://, entity-examples://).
  • Tool discovery — a <platform>_search_tools tool that lets an agent search the server's own catalog by intent instead of paging the full list. On 11 servers (all except the small gads-mcp and sa360-mcp / reporting-only dbm-mcp).
  • Server discovery cards — SEP-2127 metadata at /.well-known/mcp/server-card.json (name, version, transports, auth modes, capabilities) on every server, in every auth mode.
  • OAuth resource discovery — in jwt auth mode, the RFC 9728 endpoint at /.well-known/oauth-protected-resource.
  • Report CSV spill — large report bodies spill to GCS behind a signed URL so responses stay bounded. On the six reporting-heavy servers: ttd-mcp, tiktok-mcp, snapchat-mcp, amazon-dsp-mcp, pinterest-mcp, msads-mcp.
Server Discovery Prompts Resources CSV spill
gads-mcp
meta-mcp
dv360-mcp
ttd-mcp
linkedin-mcp
tiktok-mcp
cm360-mcp
sa360-mcp
pinterest-mcp
snapchat-mcp
amazon-dsp-mcp
msads-mcp
dbm-mcp

Built for Production

Self-hosting an AI agent that touches live ad spend is a trust problem first and a capability problem second. Two things make this fleet shippable to production without hand-rolling guardrails:

  • Audit-grade observability. Every tool call is captured as append-only JSONL. Failures additionally capture the full upstream HTTP trail — every request, every retry, every response — with secrets redacted at the source. Query it directly in BigQuery for hosted deployments, or pipe stdout to your existing log stack for self-host. Read the observability guide.
  • Destructive-action elicitation gates. 51 destructive tools across the twelve write-capable servers (dbm-mcp is reporting-only) prompt the user before deletes, bulk status changes, bid adjustments, budget changes, conversion uploads, and async Workflows batch jobs. Stdio and clients without elicitation support fall back to a documented non-interactive contract. Bulk mutations under 10 items skip the prompt unless they touch a sensitive field (status / budget / bid).
  • Verifiable release provenance. Governed tools carry a canonical SHA-256 definitionHash (from @cesteral/contract-hash) emitted into a per-package cesteral-manifest.json. Tagged releases publish to npm with build provenance, signing the manifest transitively inside the tarball, so a downstream governance system can verify exactly which tool definitions shipped and promote matching tools to attested trust.

If your security review needs evidence — the redaction list, the field schema, the upstream capture path, the contract hash — all of it is in this repository.


Quick Start

For a guided walkthrough, see the 10-minute quickstart.

Prerequisites

  • Node.js >= 20.0.0
  • pnpm >= 10.0.0 -- corepack enable picks up the pinned version from packageManager (or npm install -g pnpm@10)
  • Docker (for containerization)
  • Terraform >= 1.6.0 (for deployment)

1. Clone and install

git clone https://github.com/cesteral/mcp-open-advertising.git
cd mcp-open-advertising
pnpm install

2. Build

pnpm run build

3. Run a server locally

# Start any server using the dev script
./scripts/dev-server.sh gads-mcp    # port 3004
./scripts/dev-server.sh meta-mcp    # port 3005
./scripts/dev-server.sh dv360-mcp   # port 3002

# See each package README for required environment variables

4. Configure your AI agent

{
  "mcpServers": {
    "cesteral-gads": {
      "url": "https://gads.your-domain.com/mcp",
      "apiKey": "your-gads-api-key"
    },
    "cesteral-meta": {
      "url": "https://meta.your-domain.com/mcp",
      "apiKey": "your-meta-api-key"
    }
  }
}

Add as many servers as you need. Each runs independently and can be deployed separately.

5. Deploy

cd terraform
terraform init
terraform apply -var-file=dev.tfvars

See the deployment guide for production setup.


Architecture

Cesteral uses a GCP-native architecture with thirteen independently deployable Cloud Run MCP services. Each server exposes the MCP protocol directly via HTTPS on Cloud Run.

Key design decisions:

  • Single cloud provider (GCP): Cloud Run, BigQuery, Pub/Sub, Secret Manager -- unified monitoring, ~$150-220/month
  • Direct HTTP transport: No edge gateway layer needed
  • Independent deployment: Each server can be deployed and scaled separately
  • Composable: Use one server or all thirteen -- they work independently or together

AI clients connect directly to one or more MCP servers over HTTPS; there is no shared gateway to provision. Cesteral Intelligence, when used, layers tenancy, credentials, approvals, and governance above the same fleet.

Repository Structure

mcp-open-advertising/
├── packages/
│   ├── gads-mcp/          # Google Ads
│   ├── meta-mcp/          # Meta Ads
│   ├── dv360-mcp/         # DV360
│   ├── ttd-mcp/           # The Trade Desk
│   ├── linkedin-mcp/      # LinkedIn Ads
│   ├── tiktok-mcp/        # TikTok Ads
│   ├── cm360-mcp/         # Campaign Manager 360
│   ├── sa360-mcp/         # Search Ads 360
│   ├── pinterest-mcp/     # Pinterest Ads
│   ├── snapchat-mcp/      # Snapchat Ads
│   ├── amazon-dsp-mcp/    # Amazon DSP
│   ├── msads-mcp/         # Microsoft Ads
│   ├── dbm-mcp/           # Bid Manager (reporting)
│   ├── contract-schema/   # Shared library -- canonical annotation + response schemas
│   ├── contract-hash/     # Shared library -- canonical tool-definition hash
│   └── shared/            # Shared auth, telemetry, utilities
├── terraform/             # Infrastructure as Code
├── scripts/               # Deployment and dev automation
└── docs/                  # Documentation and guides

Development

# Install dependencies
pnpm install

# Build all packages
pnpm run build

# Run tests
pnpm run test

# Type checking
pnpm run typecheck

# Lint
pnpm run lint

Testing MCP Tools

# Use MCP Inspector
npx @modelcontextprotocol/inspector packages/gads-mcp

# Or use curl
curl -X POST http://localhost:3004/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "method": "tools/list", "id": 1}'

Technology Stack

  • Runtime: TypeScript 5.0+, Node.js 20 LTS, Hono (HTTP + MCP transport)
  • Validation: Zod schemas
  • Infrastructure: GCP Cloud Run, BigQuery, Pub/Sub, Secret Manager, Terraform
  • Build: Turborepo, pnpm workspaces, Docker

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

  1. Fork the repository
  2. Create a feature branch: git checkout -b feature/your-feature
  3. Make changes and write tests
  4. Run tests: pnpm run test
  5. Submit a Pull Request

See also: CODE_OF_CONDUCT.md | SECURITY.md | ROADMAP.md


License

Apache License 2.0


Support

  • Website: cesteral.com -- managed hosting and commercial features
  • Documentation: docs/ for guides and architecture
  • GitHub Issues: Report bugs or request features
  • Email: support@cesteral.com

Recommended MCP Servers

How it compares

API-facing MCP server for Pinterest Ads, not a Canva or creative design skill.

FAQ

Who is Pinterest Ads MCP Server for?

Developers and marketers using AI agents who operate Pinterest Ads for ecommerce, content, or app promotion.

When should I use Pinterest Ads MCP Server?

Use it during launch distribution when you need agent-driven campaign edits, targeting changes, estimates, or async reports.

How do I add Pinterest Ads MCP Server to my agent?

Add @cesteral/pinterest-mcp via npm for stdio with Pinterest API credentials, or connect to your deployed remote MCP URL with the host variable set.

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