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Portkey MCP Server for Windsurf 10 tools — connect in under 2 minutes

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Windsurf brings agentic AI coding to a purpose-built IDE. Connect Portkey through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.

Vinkius supports streamable HTTP and SSE.

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The modern way to manage MCP Servers — no config files, no terminal commands. Install Portkey and 2,500+ MCP Servers from a single visual interface.

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Download Free Open SourceNo signup required
Classic Setup·json
{
  "mcpServers": {
    "portkey": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
Portkey
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Portkey MCP Server

What you can do

Connect AI agents to the Portkey AI Gateway for enterprise-grade observability and management:

Windsurf's Cascade agent chains multiple Portkey tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 10 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.

  • Monitor logs and traces of all LLM calls passing through your gateway
  • Analyze token usage, latency, and costs across models and teams
  • Submit feedback (Likes/Dislikes) to improve model quality and agent performance
  • Export logs for audit trails, compliance, and offline cost analysis
  • Review gateway configurations including retry policies, fallbacks, and cache settings
  • Manage virtual keys to track provider API key usage and limits
  • Discover supported models from 1,600+ LLMs available via Portkey
  • Enforce budget policies to prevent runaway AI costs per team or project

The Portkey MCP Server exposes 10 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Portkey to Windsurf via MCP

Follow these steps to integrate the Portkey MCP Server with Windsurf.

01

Open MCP Settings

Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"

02

Add the server

Paste the JSON configuration above into mcp_config.json

03

Save and reload

Windsurf will detect the new server automatically

04

Start using Portkey

Open Cascade and ask: "Using Portkey, help me...". 10 tools available

Why Use Windsurf with the Portkey MCP Server

Windsurf provides unique advantages when paired with Portkey through the Model Context Protocol.

01

Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention

02

Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively

03

JSON-based configuration means zero code changes: paste a URL, reload, and all 10 tools are immediately available

04

Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts

Portkey + Windsurf Use Cases

Practical scenarios where Windsurf combined with the Portkey MCP Server delivers measurable value.

01

Automated code generation: ask Cascade to fetch data from Portkey and generate models, types, or handlers based on real API responses

02

Live debugging: query Portkey tools mid-session to inspect production data while debugging without leaving the editor

03

Documentation generation: pull schema information from Portkey and have Cascade generate comprehensive API docs automatically

04

Rapid prototyping: combine Portkey data with Cascade's code generation to scaffold entire features in minutes

Portkey MCP Tools for Windsurf (10)

These 10 tools become available when you connect Portkey to Windsurf via MCP:

01

create_policy

Requires policy name, budget limit (USD or token count), and optionally the target users or virtual keys to restrict. Returns the created policy details. Use this to enforce cost controls on specific teams or projects using the gateway. Create a new budget or usage policy for AI gateway access

02

delete_policy

Requires the policy ID. Use this when a project ends or budget constraints are no longer needed. Remove a budget or usage policy from Portkey

03

export_logs

Optionally filters by date range, model, or user. Returns an export ID or download URL. Use this for audit trails, cost reporting, or offline analysis of AI usage patterns. Export AI gateway logs for external analysis or compliance reporting

04

get_log_details

Requires the log ID from list_logs results. Use this for deep debugging of specific AI interactions. Get detailed information about a specific AI gateway log entry

05

get_virtual_keys

Virtual keys map to underlying provider keys (OpenAI, Anthropic, etc.) with metadata, usage limits, and policy associations. Returns key IDs, names, provider targets, current usage, and status. Use this to audit API key usage or identify keys approaching limits. List all virtual API keys managed by Portkey

06

list_configs

Returns config IDs, names, creation dates, and associated virtual keys. Use this to review how LLM requests are routed or to audit gateway behavior. List all gateway configurations stored in Portkey

07

list_logs

Returns log IDs, timestamps, model names, token usage, latency, costs, and status codes. Use this to monitor AI usage, identify expensive calls, or debug latency issues. Supports pagination via limit/offset. List recent AI gateway logs and traces from Portkey

08

list_models

). Returns model names, provider names, supported endpoints (chat, embeddings, etc.), and capabilities. Use this to discover which models are routable via your gateway. List all LLM models supported by the Portkey gateway

09

list_policies

Returns policy names, limits, current consumption, and affected users/keys. Use this to review guardrails preventing runaway AI costs. List all budget and usage policies defined in Portkey

10

submit_feedback

Requires the log ID, rating (LIKE, DISLIKE, or UNLIKE to remove), and optional text feedback. Use this to build RLHF datasets or monitor user satisfaction with AI outputs. Submit user feedback (Like/Dislike) for a specific AI response log

Example Prompts for Portkey in Windsurf

Ready-to-use prompts you can give your Windsurf agent to start working with Portkey immediately.

01

"Show me the most expensive LLM calls from the last 24 hours"

02

"Create a budget policy limiting the Marketing team to $500/month on LLM usage"

03

"Export all logs from last week for our compliance audit"

Troubleshooting Portkey MCP Server with Windsurf

Common issues when connecting Portkey to Windsurf through the Vinkius, and how to resolve them.

01

Server not connecting

Check Settings → MCP for the server status. Try toggling it off and on.

Portkey + Windsurf FAQ

Common questions about integrating Portkey MCP Server with Windsurf.

01

How does Windsurf discover MCP tools?

Windsurf reads the mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.
02

Can Cascade chain multiple MCP tool calls?

Yes. Cascade is an agentic system. it can plan and execute multi-step workflows, calling several tools in sequence to accomplish complex tasks without manual prompting between steps.
03

Does Windsurf support multiple MCP servers?

Yes. Add as many servers as needed in mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.

Connect Portkey to Windsurf

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.