hejdar-mcp
hejdar-mcp
MCP-Server für Hejdar — Laufzeit-Richtliniendurchsetzung für KI-Agenten.
Dieser Server stellt hejdar_evaluate als MCP-Tool bereit. Jeder MCP-kompatible Agent (Claude, ChatGPT, Cursor, benutzerdefiniert) kann es aufrufen, um vor der Ausführung zu prüfen, ob eine Aktion gemäß der Unternehmensrichtlinie zulässig ist.
Der MCP-Server ist ein schlanker Wrapper um die Hejdar-API (POST /v1/evaluate). Er enthält keine eigene Richtlinienlogik – alle Entscheidungen basieren auf den in Ihrer Hejdar-Organisation konfigurierten Richtlinien.
Schnellstart
1. Installation
pip install hejdar-mcpOder führen Sie es direkt mit uvx aus:
uvx hejdar-mcp2. API-Schlüssel abrufen
Registrieren Sie sich unter app.hejdar.com und erstellen Sie einen API-Schlüssel unter Settings → API Keys.
3. MCP-Client konfigurieren
Claude Desktop
Fügen Sie dies zur Konfiguration Ihres Claude Desktops hinzu (~/Library/Application Support/Claude/claude_desktop_config.json unter macOS, %APPDATA%\Claude\claude_desktop_config.json unter Windows):
{
"mcpServers": {
"hejdar": {
"command": "uvx",
"args": ["hejdar-mcp"],
"env": {
"HEJDAR_API_KEY": "hejdar_sk_your_key_here"
}
}
}
}Claude Code
Fügen Sie dies zu Ihren Claude Code MCP-Einstellungen hinzu:
{
"mcpServers": {
"hejdar": {
"command": "uvx",
"args": ["hejdar-mcp"],
"env": {
"HEJDAR_API_KEY": "hejdar_sk_your_key_here"
}
}
}
}Direkt (stdio)
export HEJDAR_API_KEY=hejdar_sk_your_key_here
hejdar-mcpRelated MCP server: Aegis MCP Server
Erste Schritte
Installation:
pip install hejdar-mcpoderuvx hejdar-mcpAPI-Schlüssel abrufen — kontaktieren Sie uns unter hello@hejdar.com oder besuchen Sie hejdar.com
MCP-Client konfigurieren (siehe Konfigurationsbeispiel oben)
Tool: hejdar_evaluate
Bewerten Sie eine Agentenaktion anhand der Sicherheitsrichtlinien Ihres Unternehmens.
Eingabe:
Parameter | Typ | Erforderlich | Beschreibung |
| string | Ja |
|
| string | Ja | Zielressource, z. B. |
| string | Nein | Name des aufrufenden Agenten, z. B. |
| object | Nein | Freie Metadaten (Abteilung, user_id, Grund, etc.) |
Ausgabe:
{
"decision": "DENY",
"policy_id": "pol_abc123",
"reason": "Deletion of customer data requires manager approval",
"risk_level": "HIGH"
}decision ist einer der folgenden Werte: ALLOW, DENY, WOULD_DENY.
System-Prompt-Muster
Für optimale Ergebnisse fügen Sie dies dem System-Prompt Ihres Agenten hinzu:
You have access to the hejdar_evaluate tool. Before performing any action
that reads, writes, deletes, transfers data, or executes commands on
external systems, you MUST call hejdar_evaluate first.
If hejdar_evaluate returns DENY or WOULD_DENY, do NOT proceed with the
action. Instead, inform the user that the action was blocked by policy
and include the reason provided.Umgebungsvariablen
Variable | Erforderlich | Standardwert | Beschreibung |
| Ja | — | Ihr Hejdar API-Schlüssel |
| Nein |
| API-Basis-URL (für Self-Hosting) |
Sicherheit
Der API-Schlüssel wird nur aus Umgebungsvariablen gelesen — er wird niemals fest codiert oder in Tool-Ein-/Ausgaben offengelegt
Alle Eingaben werden validiert und bereinigt, bevor sie an die API weitergeleitet werden
Fehlerantworten geben niemals interne Details, API-Schlüssel oder Stack-Traces preis
Alle API-Aufrufe erzwingen TLS
Entwicklung
git clone https://github.com/ARKALDA/hejdar-mcp.git
cd hejdar-mcp
pip install -e ".[dev]"
pytestLizenz
MIT
Available Tools
1 toolhejdar_evaluateA
Evaluate an AI agent action against Hejdar security policies BEFORE executing it. Returns ALLOW, DENY, or WOULD_DENY. Call this before any sensitive action (read, write, delete, transfer, execute) to check if the action is permitted by organizational policy. If the decision is DENY, do NOT execute the action.
| Name | Required | Description | Default |
|---|---|---|---|
| action_type | Yes | The type of action the agent intends to perform | |
| resource | Yes | The target resource or system the action applies to, e.g. 'customer_database', 'employee_records', 'email_system' | |
| agent_name | No | Name identifying this agent, e.g. 'hr-assistant', 'finance-bot' | |
| context | No | Optional metadata about the action — department, user_id, reason, data_classification, etc. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it performs a pre-execution security evaluation, returns one of three policy decisions, and has a critical safety implication (preventing execution on DENY). It doesn't mention rate limits, authentication needs, or error handling, but covers the core operational behavior well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise. The first sentence establishes the core purpose and output. The second sentence provides critical usage guidelines. The third sentence delivers an essential safety instruction. Every sentence earns its place with no wasted words, and the most important information (what it does and when to use it) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a security evaluation tool with no annotations and no output schema, the description provides excellent context about its purpose, usage, and behavioral implications. It doesn't describe the return format details (what ALLOW/DENY/WOULD_DENY responses contain) or potential error cases, but covers the essential operational context sufficiently given the tool's critical safety role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, so the baseline is 3. The tool description doesn't add any parameter-specific information beyond what's already documented in the schema (action_type, resource, agent_name, context). It mentions these parameters implicitly through examples ('read, write, delete, transfer, execute') but provides no additional semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('evaluate an AI agent action against Hejdar security policies') and resources ('security policies'), and explicitly distinguishes its role as a pre-execution check. It identifies the exact function (policy evaluation) and output (ALLOW, DENY, WOULD_DENY), leaving no ambiguity about what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('before any sensitive action') and what to do based on the outcome ('if the decision is DENY, do NOT execute the action'). It lists specific action types (read, write, delete, transfer, execute) that should trigger its use, offering clear operational instructions despite no sibling tools for comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- First observed
hejdar_evaluate
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool's purpose is clearly defined as evaluating AI agent actions against security policies, making it distinct and unambiguous in isolation.
A single tool inherently has perfect naming consistency since there are no other tools to compare against. The name 'hejdar_evaluate' follows a clear pattern of server prefix and action, which would be consistent if more tools existed.
A single tool is too few for a server that claims to handle security policy evaluation across various actions (read, write, delete, transfer, execute). This minimal set forces agents to rely solely on this one tool without dedicated tools for different policy aspects or actions, making the scope feel incomplete and thin.
The server's domain appears to be security policy evaluation for AI actions, but with only one tool, there are significant gaps. It lacks tools for managing policies, querying specific rules, or handling different types of security checks, which limits agents to a single evaluation call without supporting operations for a comprehensive workflow.
Maintenance
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