How TameFlare Secures MCP Traffic Without MCP-Specific Code

What is MCP?

MCP (Model Context Protocol) is a JSON-RPC 2.0 protocol that connects AI hosts (Claude, ChatGPT, custom agents) to tool servers (GitHub MCP server, database MCP server, etc.). It's becoming the standard way agents interact with external tools.

MCP defines two transport mechanisms:

Streamable HTTP - The MCP server exposes an HTTP endpoint. The client sends JSON-RPC requests via standard HTTP POST. The server responds with JSON or Server-Sent Events (SSE).

stdio - The client launches the MCP server as a local subprocess and communicates via stdin/stdout.

The critical insight: Streamable HTTP is standard HTTP. And TameFlare is an HTTP proxy.

What MCP traffic looks like on the wire

When an agent calls an MCP tool, the HTTP request looks like this:

POST /mcp HTTP/1.1
Content-Type: application/json
Accept: application/json, text/event-stream

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_pull_request",
    "arguments": {
      "repo": "acme/backend",
      "title": "Fix auth bug",
      "head": "fix-auth",
      "base": "main"
    }
  }
}

This is a completely standard HTTP POST with a JSON body. There's nothing MCP-specific about the transport layer. It's just HTTP.

Why TameFlare already intercepts MCP

TameFlare's gateway is a transparent HTTP/HTTPS proxy. When you run any process through tf run, all outbound HTTP traffic is routed through the proxy. This includes:

REST API calls to GitHub, Stripe, OpenAI

GraphQL queries

Webhook requests

MCP Streamable HTTP requests

The proxy doesn't need to know it's MCP traffic. It intercepts the HTTP request, checks the target domain against your connector configuration, enforces permissions, injects credentials from the vault, and logs the result.

Capability	Status
Intercept MCP HTTP traffic	Works today
Log MCP requests in traffic log	Works today
Domain-level permissions	Works today
Credential injection	Works today
Kill switch	Works today
Per-tool MCP permissions	Coming (MCP connector)

How to govern MCP traffic with TameFlare

Step 1: Set up TameFlare as usual

npm install -g @tameflare/cli
tf init

Step 2: Add a connector for your MCP server's domain

tf connector add (now configured in dashboard) generic \
  --domains mcp-server.example.com \
  --token-env MCP_AUTH_TOKEN

Step 3: Set permissions

tf permissions set --gateway "my-agent" \
  --connector generic \
  --action "http.*" \
  --decision allow

Step 4: Run your agent through the proxy

tf run -- "my-agent" python mcp_agent.py

Every MCP tool call now passes through TameFlare. Every request is logged. Credentials are injected from the vault. The kill switch works instantly.

What about competitors?

Several competitors have built MCP-native proxies:

Tool	Approach	Trade-off
Agentgateway (Solo.io)	MCP-native Rust proxy	Only handles MCP/A2A traffic
Archestra	MCP platform with security	Requires MCP-specific infrastructure
GuardionAI	MCP-focused security	Early-stage, narrow scope
TameFlare	General HTTP proxy	Intercepts ALL HTTP traffic including MCP

TameFlare's approach is different: instead of building a protocol-specific proxy, we built a general-purpose HTTP proxy that happens to intercept MCP traffic along with everything else. This means:

One proxy for all traffic - MCP, REST, GraphQL, webhooks, everything

No migration needed - if you're already using TameFlare, MCP traffic is already governed

No vendor lock-in - if MCP evolves or a new protocol emerges, the HTTP proxy still works

The MCP connector (coming soon)

Today, TameFlare treats MCP traffic as generic HTTP. That means permissions are domain-level (allow/deny mcp-server.example.com), not tool-level.

We're building an MCP connector that will parse JSON-RPC tools/call messages into structured TameFlare actions:

Extract params.name as the action type (e.g., mcp.tools.create_pull_request)

Extract params.arguments as action parameters

Enable per-tool permissions: "allow read_file but deny delete_repository"

Log structured actions in the audit trail (not just raw HTTP)

This will bring MCP traffic to the same level of granularity as our GitHub, OpenAI, and Stripe connectors.

What about stdio MCP?

stdio transport is process-level IPC (stdin/stdout), not network traffic. TameFlare's proxy cannot intercept it. However:

Production MCP servers use Streamable HTTP. stdio is primarily for local development (Claude Desktop, Cursor).

The MCP ecosystem is moving toward HTTP. Remote MCP servers, cloud-hosted tools, and multi-agent systems all use HTTP transport.

If you need governance for stdio MCP, the practical solution is to switch to Streamable HTTP transport for production.

Getting started

1. Create a free account - 3 gateways, 1,000 actions/month
2. Install the CLI: npm install -g @tameflare/cli
3. Add connectors for your MCP server domains
4. Run your agent through the proxy: tf run -- "my-agent" python agent.py
5. Check the traffic log - you'll see every MCP tool call

No MCP-specific configuration. No special setup. If it's HTTP, TameFlare governs it.