freshprobe

Data freshness verification for AI agents.
Stop your agents from acting on stale data.

---

"I asked my agent to check flight prices. It gave me options. I booked one. The fare had changed 3 hours ago."

AI agents routinely act on stale data without knowing it. A financial agent queries cached quotes from 47 minutes ago. A support bot tells a customer their order doesn't exist because the CRM hasn't synced. An RAG pipeline confidently answers with yesterday's docs.

freshprobe sits between your agent and the external world. Before the agent acts, it asks: is this data fresh enough? The answer is always a deterministic JSON verdict: FRESH, STALE, or UNKNOWN.

$ freshprobe check https://api.example.com/v2/quotes

{
  "verdict": "STALE",
  "confidence": 0.94,
  "endpoint": "https://api.example.com/v2/quotes",
  "freshness": {
    "data_age_seconds": 2847,
    "freshness_score": 0.12,
    "cache_control": "max-age=3600"
  },
  "liveness": {
    "status": "DEGRADED",
    "latency_p50_ms": 342,
    "latency_p95_ms": 1847,
    "body_size_bytes": 4096,
    "error_rate": 0.03
  },
  "redirects": {
    "total_hops": 1,
    "final_url": "https://api-v2.example.com/quotes",
    "has_redirect": true
  },
  "nist_mapping": {
    "ai_rmf_function": "MEASURE",
    "control": "MS-2.6-001"
  }
}

Single Go binary. No dependencies. Runs as CLI, MCP server, or HTTP microservice.

Why this matters

Problem	Cost
E-commerce agent used 6-month-old product data	$5M+ revenue loss
Enterprise RAG with overlapping refresh infrastructure	$340K/year wasted
AI project failures from data quality issues	60%+ of failures (Gartner)

Unlike crashes that trigger alerts, stale data produces confident, well-formatted, completely wrong responses. Chain a few of those in a multi-agent pipeline and every component reports green while the output is catastrophically wrong.

Install

Go install (recommended):

go install github.com/Sudhan30/freshprobe/cmd/freshprobe@latest

Docker:

docker run --rm ghcr.io/sudhan30/freshprobe:latest check https://example.com

From source:

git clone https://github.com/Sudhan30/freshprobe.git && cd freshprobe && make build
./bin/freshprobe --version

GitHub Releases: Download pre-built binaries for Linux, macOS, and Windows from Releases.

Quick start

# Basic freshness check
freshprobe check https://api.example.com/data

# Human-readable output
freshprobe check https://api.example.com/data --output text

# Content fingerprinting: detect if data actually changes
freshprobe check https://api.example.com/data --repeat 3 --interval 2s

# Check against a freshness policy
freshprobe check https://api.example.com/data --policy-dir ./policies --policy financial-data

# Batch check multiple endpoints
freshprobe batch https://api1.example.com https://api2.example.com https://cdn.example.com

# Continuous monitoring (Ctrl+C to stop)
freshprobe watch https://api.example.com/data --interval 30s --output text

# Only alert on verdict changes (FRESH -> STALE)
freshprobe watch https://api.example.com/data --interval 1m --on-change --output text

# View probe history for an endpoint
freshprobe history https://api.example.com/data --limit 20 --output text

Six verification signals

Signal	What it checks
HTTP cache headers	Parses Last-Modified, Cache-Control, Age, ETag, Date, Expires. Computes 0.0 to 1.0 freshness score
Endpoint liveness	Measures response latency (P50/P95/P99), status codes, body size, degradation patterns
Content fingerprinting	SHA-256 hashes response bodies across repeated probes to detect stale caches
TLS certificate health	Certificate validity, days remaining, OCSP stapling status
DNS resolution timing	DNS lookup latency as infrastructure health signal
Redirect chain analysis	Tracks 301/302/307/308 hops, detects stale CDN configs

Three deployment modes

CLI

freshprobe check <url> [flags]
freshprobe batch <urls...> [flags]
freshprobe watch <url> --interval 30s [flags]
freshprobe history <url> --limit 20

MCP server (for AI agents)

Add to your AI tool config:

Claude Desktop / Claude Code

{
  "freshprobe": {
    "type": "stdio",
    "command": "freshprobe",
    "args": ["serve", "--mode", "mcp", "--policy-dir", "/path/to/policies", "--stateless"]
  }
}

Cursor

In .cursor/mcp.json:

{
  "mcpServers": {
    "freshprobe": {
      "command": "freshprobe",
      "args": ["serve", "--mode", "mcp", "--stateless"]
    }
  }
}

VS Code (Copilot)

In .vscode/mcp.json:

{
  "servers": {
    "freshprobe": {
      "type": "stdio",
      "command": "freshprobe",
      "args": ["serve", "--mode", "mcp", "--stateless"]
    }
  }
}

This exposes three tools to AI agents:

Tool	Description
freshprobe_check	Probe a single endpoint. Returns JSON verdict
freshprobe_batch	Probe multiple endpoints concurrently
freshprobe_policy	Check an endpoint against a named freshness policy

HTTP server

freshprobe serve --mode http --addr :8080

POST /api/v1/check    {"url": "https://..."}
POST /api/v1/batch    {"urls": ["https://...", "https://..."]}
POST /api/v1/policy   {"url": "https://...", "policy_name": "api-realtime"}
GET  /healthz
GET  /metrics          # Prometheus-compatible metrics

Policies (freshness-as-code)

Define freshness thresholds per domain in YAML:

version: "1"
policies:
  financial-data:
    name: "Financial Data"
    domains: ["*.market.*", "*.trading.*"]
    max_staleness: "30s"
    min_freshness_score: 0.9
    max_latency_p95_ms: 200
    require_tls: true
    min_tls_days_left: 30
    require_changing: true

  api-standard:
    name: "Standard API"
    domains: ["api.*"]
    max_staleness: "5m"
    min_freshness_score: 0.6
    max_latency_p95_ms: 2000
    require_tls: true

When a probe violates a policy:

{
  "policy_result": {
    "policy_name": "Financial Data",
    "passed": false,
    "violations": [
      {"check": "max_staleness", "expected": "<= 30s", "actual": "2m15s"},
      {"check": "max_latency_p95", "expected": "<= 200 ms", "actual": "847 ms"}
    ]
  }
}

Four built-in policies included: api-realtime, api-standard, static-content, financial-data.

Continuous monitoring

# Watch an endpoint, print every probe
freshprobe watch https://api.example.com/quotes --interval 30s --output text

# Only print when verdict changes (FRESH -> STALE transitions)
freshprobe watch https://api.example.com/quotes --interval 1m --on-change --output text

# Run 10 probes and exit
freshprobe watch https://api.example.com/quotes --count 10 --interval 5s

Example output:

Watching https://api.example.com/quotes every 30s
[14:22:01] FRESH conf=0.90 score=0.87 p95=142ms
[14:22:31] FRESH conf=0.90 score=0.85 p95=156ms
[14:23:01] STALE conf=0.85 score=0.22 p95=1847ms [FRESH -> STALE]

Prometheus metrics

The HTTP server exposes /metrics with Prometheus-compatible text format:

freshprobe_probes_total 142
freshprobe_verdict_total{verdict="FRESH"} 98
freshprobe_verdict_total{verdict="STALE"} 31
freshprobe_verdict_total{verdict="UNKNOWN"} 13
freshprobe_latency_p95_seconds 0.234000
freshprobe_freshness_score 0.7200

How it compares

Feature	freshprobe	Uptime Kuma	Gatus	freshcontext-mcp
Purpose	Data freshness for AI agents	Uptime monitoring	Health dashboards	Web extraction timestamps
Knows data is stale	Yes (cache headers + fingerprinting)	No (only checks HTTP status)	No (only checks response assertions)	Partial (timestamps, no verification)
MCP server	Yes (3 tools)	No	No	Yes
Policy engine	Yes (YAML, per-domain)	No	Yes (YAML conditions)	No
Continuous monitoring	Yes (watch command)	Yes (dashboard)	Yes (dashboard)	No
Prometheus metrics	Yes	No (push-based)	Yes	No
Deployment	Single binary	Docker + DB	Single binary	npm package

Architecture

                    +------------------+
                    |   freshprobe     |
                    |   single binary  |
                    +--------+---------+
                             |
              +--------------+--------------+
              |              |              |
         +----+----+   +----+----+   +-----+-----+
         |   CLI   |   |   MCP   |   |   HTTP    |
         | (cobra) |   | (stdio) |   | (net/http)|
         +---------+   +---------+   +-----------+
              |              |              |
              +--------------+--------------+
                             |
                    +--------+---------+
                    |   Probe Engine   |
                    |                  |
                    | HTTP headers     |
                    | Latency P50/95/99|
                    | Content SHA-256  |
                    | TLS/OCSP        |
                    | DNS timing       |
                    | Redirect chains  |
                    +--------+---------+
                             |
              +--------------+--------------+
              |              |              |
         +----+----+   +----+----+   +-----+-----+
         | Verdict |   | Policy  |   |   Store   |
         | Engine  |   | Engine  |   | SQLite /  |
         |         |   | (YAML)  |   | Stateless |
         +---------+   +---------+   +-----------+

Kubernetes deployment

apiVersion: apps/v1
kind: Deployment
metadata:
  name: freshprobe
spec:
  replicas: 1
  selector:
    matchLabels: { app: freshprobe }
  template:
    metadata:
      labels: { app: freshprobe }
    spec:
      containers:
        - name: freshprobe
          image: ghcr.io/sudhan30/freshprobe:latest
          args: ["serve", "--mode", "http", "--addr", ":8080",
                 "--policy-dir", "/etc/freshprobe/policies", "--stateless"]
          ports:
            - containerPort: 8080
          resources:
            requests: { cpu: 50m, memory: 64Mi }
            limits: { cpu: 200m, memory: 128Mi }
          readinessProbe:
            httpGet: { path: /healthz, port: 8080 }
          livenessProbe:
            httpGet: { path: /healthz, port: 8080 }

Claude Code plugin

/plugin install github:Sudhan30/freshprobe

After installing, ask Claude:

• "Is the trading API returning fresh data?"
• "Check all our endpoints before running the batch job"
• "Does this API meet our real-time SLA?"

Development

make build       # Build binary
make test        # Run tests with race detector
make lint        # go vet
make cross       # Cross-compile (linux, macOS, Windows)
make docker      # Docker build

Contributing

See CONTRIBUTING.md. High-value areas:

• Policy packs for specific domains (healthcare, weather, finance)
• WebSocket/gRPC/GraphQL probe signals
• OpenTelemetry integration
• Homebrew formula

License

MIT. See LICENSE.

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If freshprobe helps your agents make better decisions, give it a star.