Heddle — The policy-and-trust layer for MCP tool servers. Turn YAML configs into validated, policy-enforced MCP tools.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"heddle-mesh": {
"command": "/path/to/heddle/venv/bin/heddle-mesh"
}
}
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Heddle turns declarative configs into Model Context Protocol servers with trust enforcement, credential brokering, and tamper-evident audit logging built in.
No automated test available for this server. Check the GitHub README for setup instructions.
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The policy-and-trust layer for MCP tool servers.
Heddle turns declarative configs into Model Context Protocol servers
with trust enforcement, credential brokering, and tamper-evident audit logging built in.
See It Work · Why Heddle · Current Status · Security · Quick Start
One config, one MCP server. This YAML is a complete tool server — no Python, no boilerplate:
agent:
name: prometheus-bridge
version: "1.0.0"
description: "Bridges Prometheus for natural language metric queries"
exposes:
- name: query_prometheus
description: "Run a PromQL query"
parameters:
query: { type: string, required: true }
- name: get_alerts
description: "List active Prometheus alerts"
http_bridge:
- tool_name: query_prometheus
method: GET
url: "http://localhost:9090/api/v1/query"
query_params: { query: query }
- tool_name: get_alerts
method: GET
url: "http://localhost:9090/api/v1/alerts"
runtime:
trust_tier: 1 # enforced: GET/HEAD only, no writes, no cross-agent calls
Run it:
heddle run agents/prometheus-bridge.yaml
Claude can now query Prometheus in natural language.
Current demo environment: 46 tools from 9 active configs through a single MCP connection (11 configs total, 2 excluded for incompatible transports).
daily-ops (T3): daily_briefing, system_health_check, threat_landscape
gitea-api-bridge (T1): list_user_repos, list_repo_issues
grafana-bridge (T1): list_dashboards, get_dashboard, list_datasources, get_alert_rules, grafana_health
ai-platform (T1): health, ai_status, routing_stats, routing_costs, list_apps, detect_drift, ...
ollama-bridge (T2): list_models, list_running, generate, show_model
prometheus-bridge(T1): query_prometheus, query_range, get_targets, get_alerts, get_metric_names
rsshub-bridge (T1): get_hacker_news, get_github_trending, search_arxiv, get_reuters_news
vram-orchestrator(T3): vram_status, smart_load, smart_generate, optimize_vram, unload_model, model_library
intel-rag-bridge (T2): ask_intel, get_dossier, get_trending, get_patterns, get_communities, get_stats, ...
Security is always on. Every tool call passes through trust enforcement, credential brokering, and audit logging.
Example: a T1 (read-only) agent attempted a POST and was blocked:
{
"event": "trust_violation",
"agent": "reader",
"trust_tier": 1,
"action": "http_POST",
"detail": "T1 agent cannot use POST. Allowed: ['GET', 'HEAD', 'OPTIONS']",
"severity": "high",
"chain_hash": "92c189e3..."
}
The request was rejected, the violation was logged, and the hash chain links this entry to every event before and after it.
| Heddle | Hand-written FastMCP | OpenAPI wrapper gen | n8n / workflow tools | |
|---|---|---|---|---|
| New tool | Write YAML, done | Write Python handler per tool | Generate stubs, then customize | Drag nodes, wire connections |
| Security | Trust tiers, credential broker, input validation, config signing, anomaly detection — all built in | You build it yourself | None | Platform-level auth only |
| Isolation | Docker sandboxing: --cap-drop=ALL, read-only root, pids limit, image digest pinning, watchdog | Process-level only | None | None |
| AI-generatable | heddle generate "wrap the Gitea API" → valid config in 20s | LLM can write code b |