Palaryn MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Palaryn MCP Serverget the latest issues from our GitHub repo"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Palaryn MCP Server
Agent I/O governance for every HTTP request your AI agent makes — exposed as an MCP server.
Palaryn MCP wraps the Palaryn gateway as a Model Context Protocol server, giving Claude Code, Cursor, Windsurf, and any MCP-compatible client policy-enforced access to external APIs with zero code changes.
What It Does
Every HTTP request your AI agent makes flows through the Palaryn pipeline:
Claude Code / Cursor / MCP Client
|
| stdio (JSON-RPC 2.0) or HTTP (/mcp)
v
Palaryn MCP Server
|
+---> Rate Limiting (per-actor sliding window)
+---> Anomaly Detection (statistical outlier flagging)
+---> Policy Engine (YAML rules: allow / deny / require approval)
+---> DLP Scanner (secrets, PII, 119 detection patterns)
+---> Prompt Injection (3-layer cascade: regex → DeBERTa → LLM)
+---> Call Limits (per-user / workspace daily & monthly caps)
+---> HTTP Execution (retries, backoff, SSRF protection)
+---> Output DLP Scan (response body scanning)
+---> Audit Logging (immutable append-only trace)
|
v
External APIThree MCP tools exposed:
Tool | Method | Capability | Description |
| Any | Inferred | Execute any HTTP request (GET, POST, PUT, PATCH, DELETE, HEAD, OPTIONS) |
| GET |
| GET request shorthand |
| POST |
| POST request shorthand |
Each tool accepts: url (required), headers, body, timeout_ms, purpose, labels.
Related MCP server: SentinelGate
Quick Start
Option 1: Hosted (requires a Palaryn account)
claude mcp add --transport http palaryn https://app.palaryn.com/mcpDone. All requests from Claude Code now route through Palaryn. You will be prompted to log in via OAuth on first use.
Option 2: Project-level config
Create .mcp.json in your project root (see .mcp.json.example):
{
"mcpServers": {
"palaryn": {
"type": "stdio",
"command": "npx",
"args": ["palaryn-mcp"],
"env": {
"POLICY_PACK_PATH": "./policy-packs/default.yaml"
}
}
}
}Note: Ensure
palaryn-mcpis installed (e.g., vianpm install palaryn-mcp) sonpxcan resolve it.
Configuration
Environment Variables
Variable | Default | Description |
|
| Workspace ID for tool calls |
|
| Actor ID for audit trails |
|
| Platform identifier |
|
| Path to the active policy pack |
Custom Policy Pack
Pass a custom policy via environment variable:
claude mcp add palaryn \
-e POLICY_PACK_PATH=./policy-packs/prod_strict.yaml \
-- node bin/palaryn-mcp.jsPolicy Packs
Three pre-built policy packs are included:
default.yaml -- Sensible starter rules
Block SSRF (cloud metadata endpoints)
Allow all read operations (GET)
Require human approval for writes (POST/PUT/PATCH)
Deny delete and admin operations
dev_fast.yaml -- Permissive for development
Block SSRF
Allow reads and writes without approval
Require approval for delete/admin operations
prod_strict.yaml -- Minimal permissions for production
Block SSRF + internal IPs + localhost
Allow reads only to allowlisted domains (e.g.,
api.github.com,api.slack.com)Require security review for all writes
Deny all delete and admin operations
Require admin approval for anything unmatched
Custom Policy Example
name: my-policy
version: "1.0.0"
description: "Custom policy for my project"
domain_blocklist:
- "169.254.169.254"
rules:
- name: "Allow GitHub API"
effect: ALLOW
priority: 10
conditions:
capabilities: ["read"]
domains: ["api.github.com"]
- name: "Require approval for writes"
effect: REQUIRE_APPROVAL
priority: 20
conditions:
capabilities: ["write"]
approval:
scope: "admin"
ttl_seconds: 3600
reason: "Write operations require approval"
- name: "Deny everything else"
effect: DENY
priority: 100
conditions: {}How It Works
Architecture
Palaryn MCP server is a thin adapter layer that translates MCP tool calls into the Palaryn gateway pipeline:
MCP Client (Claude Code, Cursor, etc.)
|
| JSON-RPC 2.0 over stdio
v
+-----------------------------+
| Palaryn MCP Server |
| |
| tools/list -> 3 HTTP tools |
| tools/call -> Gateway |
+-----------------------------+
|
v
+-----------------------------+
| Palaryn Gateway Pipeline |
| |
| 1. Rate Limiting |
| 2. Anomaly Detection |
| 3. Policy Evaluation |
| 4. DLP Scan (input) |
| 5. Prompt Injection (3L) |
| 6. Call Limit Check |
| 7. HTTP Execution |
| 8. DLP Scan (output) |
| 9. Audit Logging |
+-----------------------------+
|
v
External APIMCP Protocol
The server implements the Model Context Protocol specification:
Method | Description |
| Protocol handshake -- returns server info and capabilities |
| Returns the 3 HTTP tool definitions with JSON schemas |
| Executes a tool through the gateway pipeline |
| Health check |
Two Transport Modes
Mode | Protocol | Best For |
Stdio | JSON-RPC 2.0 over stdin/stdout | Claude Code, Cursor, local IDE agents |
HTTP | Streamable HTTP at | Hosted/remote deployment, shared servers |
Response Format
Every tool call returns two content blocks:
Primary content: The actual HTTP response body (or error message)
Gateway metadata: Policy decision, DLP report, call limits, timing
{
"content": [
{ "type": "text", "text": "{\"data\": \"response from API\"}" },
{ "type": "text", "text": "--- Gateway Metadata ---\n{...}" }
],
"isError": false
}Security Features
Prompt Injection Detection (3-Layer Cascade)
Three-layer defense against prompt injection attacks, evaluated in cascade (fast layers first, expensive layers only if needed):
Regex + Heuristic (sync, <1ms, $0) — 119 patterns across 17 categories with text normalization (zero-width char stripping, homoglyph collapse, ROT13/base64 decoding, leetspeak, HTML/URL decoding). Multilingual: EN, PL, DE, ES, FR.
Fine-tuned DeBERTa (sync, ~50ms, $0) — Local ML model for semantic classification. URL-aware scanning (extracts query param values, ignores URL structure). Zero API cost, works offline.
LLM Classifier (async, ~800ms, ~$0.001/req) — Semantic classification via gpt-4o-mini. Detects 12 attack categories including instruction override, prompt extraction, roleplay hijack, social engineering, game manipulation, memory manipulation, data exfiltration, multilingual injection, compound attacks, and classifier self-manipulation.
Cascade logic: LLM only runs if Regex + DeBERTa find nothing — reducing API calls by ~35%.
DLP (Data Loss Prevention)
119 detection patterns: secrets (14), PII (5), prompt injection (65), tool injection (28), exfiltration (6), sensitive files (9)
Scans request arguments AND response bodies
Detects API keys, tokens, passwords, SSNs, credit card numbers, AWS credentials in URLs, markdown image injection, large payload exfiltration
Automatically redacts sensitive data before it reaches external services
Configurable severity levels and multiple detection backends
Policy Engine
YAML-based policy rules with priority ordering
Four decisions:
ALLOW,DENY,TRANSFORM,REQUIRE_APPROVALConditions: capability level, HTTP method, target domain, tool name
Domain blocklists for SSRF protection
Optional OPA/Rego integration for advanced policy logic
SSRF Protection
Blocks requests to cloud metadata endpoints (169.254.169.254, etc.)
Blocks private/reserved IP ranges
Integer-encoded IP detection (e.g., 2852039166 → 169.254.169.254)
Domain allowlisting for production environments
Call Limits
Per-user daily and monthly call limits
Per-workspace daily and monthly call limits
Max steps per task
Prevents runaway loops from agent execution
Real-time limit tracking with remaining calls in responses
Rate Limiting
Sliding-window rate limiting per actor and per workspace
Prevents abuse and ensures fair resource allocation
Integration Patterns
Claude Code
# Hosted (requires Palaryn account)
claude mcp add --transport http palaryn https://app.palaryn.com/mcpCursor
Add to your Cursor MCP settings:
{
"mcpServers": {
"palaryn": {
"type": "stdio",
"command": "npx",
"args": ["palaryn-mcp"]
}
}
}Windsurf
Add to your Windsurf MCP configuration:
{
"mcpServers": {
"palaryn": {
"serverUrl": "https://app.palaryn.com/mcp"
}
}
}Remote MCP (HTTP)
For hosting Palaryn as a remote MCP server, the full gateway includes the /mcp HTTP endpoint with OAuth 2.0. Contact us at app.palaryn.com for access.
Tool Reference
http_request
Execute an arbitrary HTTP request through the Palaryn gateway.
Parameter | Type | Required | Description |
| string | Yes | Target URL |
| string | No | HTTP method (default: GET) |
| object | No | HTTP headers as key-value pairs |
| string | No | Request body (typically JSON) |
| number | No | Request timeout in milliseconds |
| string | No | Why this request is being made |
| string[] | No | Classification labels |
http_get
Shorthand for GET requests. Same parameters as http_request minus method and body.
http_post
Shorthand for POST requests. Same parameters as http_request minus method.
License
MIT
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- FlicenseNot gradedqualityNot gradedmaintenanceA transparent proxy and execution firewall that intercepts and audits AI agent tool calls against configurable security policies before forwarding them to downstream MCP servers. It provides safe execution environments with features like data redaction, anti-loop protection, and unified alert dispatching.

SentinelGateofficial
AlicenseNot gradedqualityAmaintenanceOpen-source MCP proxy that enforces security policies, content scanning, and audit logging between AI agents and tool servers25AGPL 3.0- AlicenseNot gradedqualityCmaintenanceMCP server for AI agent security guardrails. Provides input validation, prompt injection detection, PII redaction, output filtering, policy enforcement, rate limiting, and comprehensive audit logging.451MIT
- AlicenseNot gradedqualityBmaintenanceProvides a secure MCP gateway for AI agents to access APIs without exposing raw credentials, with scoped access, audit logging, and OAuth support.MIT
Related MCP Connectors
Security firewall for AI agents — scans MCP calls for injection, secrets, and risks.
MCP server for AI agents to plan, verify, and deploy Cloudflare-native apps.
MCP server for secureFlows: token-free URL builders and integration-linting tools for AI agents.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/palaryn-ai/mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server