AgentLedger
Meter, cap, and block AI agent spend before the provider is charged.
¿Debería usar esto?
Calidad y seguridad
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"agent-ledger": {
"url": "https://agent-ledger-production-0ff8.up.railway.app/mcp/"
}
}
}Puntos de conexión remotos
https://agent-ledger-production-0ff8.up.railway.app/mcp/streamable-httphttps://aiagentscity.com/mcp/streamable-httpQué puede hacer
Inventario de herramientas
Herramientas (12)
🔴ledger_rotate_secret(agent_id, workspace_key)
Mint a NEW agent_secret for an agent_id your workspace already owns, invalidating the old one. Use this to RECOVER an agent whose secret was lost: the previous credential stops working immediately. Requires the workspace_key that owns agent_id — an agent's own agent_secret cannot rotate itself, because a leaked agent credential must not be able to lock its real owner out. Unlike ledger_track this never claims a new agent_id: an unknown id returns agent_not_claimed. The new secret is returned ONCE. Store it before you drop the response. Returns {"agent_id", "agent_secret", "_note"}, or {"error", "error_code"}.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"type": "string"
},
"workspace_key": {
"type": "string"
}
},
"required": [
"agent_id",
"workspace_key"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🔴ledger_revoke_secret(agent_id, workspace_key)
Invalidate an agent_id's agent_secret WITHOUT deleting its spend history. Use when a credential may have leaked, or to stop an agent writing. Subsequent writes to that agent fail with agent_secret_mismatch until you rotate a new secret in. The agent_id stays claimed, so no other workspace can claim it and inherit the ledger. Requires the workspace_key that owns agent_id. Returns {"agent_id", "revoked": True, "_note"}, or {"error", "error_code"}.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"type": "string"
},
"workspace_key": {
"type": "string"
}
},
"required": [
"agent_id",
"workspace_key"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟡ledger_track(agent_id, rail, amount_cents, service, tokens_in, ...)
Record a spend entry for an AI agent on any payment rail, with optional token counts. Claiming a brand-new agent_id requires your workspace_key (get one via x402 at POST /v1/billing/x402 — no human, no login — or at /start). That first call mints an agent_secret and returns it in the response — save it, every later call for that same agent_id must pass it back (no workspace_key needed again) or the write is rejected. Amounts are capped at $100,000/entry and must be >= 0. If a budget is set for this agent, an entry that would cross the monthly/daily cap is blocked, not just logged. Include tokens_in/tokens_out + model on every LLM call so token burn shows up in the /v1/tokens report.
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"type": "string",
"description": "unique agent identifier (e.g. \"research-agent-v2\")"
},
"rail": {
"type": "string",
"description": "payment rail used — one of \"mpp\", \"x402\", \"api_key\", \"manual\""
},
"amount_cents": {
"type": "integer",
"description": "spend amount in cents (100 = $1.00), 0-10000000"
},
"service": {
"type": "string",
"description": "what was purchased (e.g. \"search_query\", \"data_export\")"
},
"tokens_in": {
"default": 0,
"type": "integer",
"description": "prompt tokens consumed (0 if unknown)"
},
"tokens_out": {
"default": 0,
"type": "integer",
"description": "completion tokens consumed (0 if unknown)"
},
"model": {
"default": "",
"type": "string",
"description": "model name (e.g. \"gpt-4o\") — token burn is reported per model"
},
"agent_secret": {
"default": "",
"type": "string",
"description": "required for every call after the first for this agent_id"
},
"workspace_key": {
"default": "",
"type": "string",
"description": "required when claiming a brand-new agent_id; not\n needed once the agent_id has been claimed"
}
},
"required": [
"agent_id",
"rail",
"amount_cents",
"service"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🔴ledger_set_budget(agent_id, monthly_cents, daily_cents, monthly_tokens, daily_tokens, ...)
Set spending caps for an agent. Warns at 80%, blocks spend when exceeded — enforced: a ledger_track call that would cross the cap is rejected. Dollar caps (monthly_cents/daily_cents) and token caps (monthly_tokens/ daily_tokens) are independent dimensions: dollar caps only cover non-"tokens" rails, token caps only cover rail="tokens" bookkeeping rows (tokens_in/tokens_out). Set both if the agent uses both. Monthly cap is required; the rest are optional (0 = no limit). Overwrites any existing budget for the agent. Claiming a brand-new agent_id requires your workspace_key; that first call mints an agent_secret (returned once — save it); later calls for that agent_id must pass the agent_secret back (no workspace_key needed again).
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"type": "string",
"description": "unique agent identifier"
},
"monthly_cents": {
"type": "integer",
"description": "monthly spending cap in cents"
},
"daily_cents": {
"default": 0,
"type": "integer",
"description": "daily spending cap in cents (0 = no daily cap)"
},
"monthly_tokens": {
"default": 0,
"type": "integer",
"description": "monthly token-burn cap (0 = no cap)"
},
"daily_tokens": {
"default": 0,
"type": "integer",
"description": "daily token-burn cap (0 = no cap)"
},
"agent_secret": {
"default": "",
"type": "string",
"description": "required for every call after the first for this agent_id"
},
"workspace_key": {
"default": "",
"type": "string",
"description": "required when claiming a brand-new agent_id; not\n needed once the agent_id has been claimed"
}
},
"required": [
"agent_id",
"monthly_cents"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢ledger_report(agent_id, days, agent_secret, workspace_key)
Spend report for an agent over a rolling window. Returns total spend, breakdown by rail and by service, budget status (ok/warning/exceeded), detected anomalies, and entry count. Requires a credential: either the agent's own agent_secret or its workspace's workspace_key (same rule as GET /v1/report).
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"type": "string",
"description": "unique agent identifier"
},
"days": {
"default": 30,
"type": "integer",
"description": "report window in days (default 30)"
},
"agent_secret": {
"default": "",
"type": "string",
"description": "the agent's own secret (either this or workspace_key)"
},
"workspace_key": {
"default": "",
"type": "string",
"description": "the owning workspace's key (either this or agent_secret)"
}
},
"required": [
"agent_id"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢ledger_alerts(agent_id, agent_secret, workspace_key)
Alert history for an agent: budget warnings (80% threshold) and spending spikes. Requires a credential: either the agent's own agent_secret or its workspace's workspace_key (same rule as GET /v1/alerts).
Esquema de entrada
{
"type": "object",
"properties": {
"agent_id": {
"type": "string",
"description": "unique agent identifier"
},
"agent_secret": {
"default": "",
"type": "string",
"description": "the agent's own secret (either this or workspace_key)"
},
"workspace_key": {
"default": "",
"type": "string",
"description": "the owning workspace's key (either this or agent_secret)"
}
},
"required": [
"agent_id"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢ledger_list_agents(admin_secret)
Owner-only: full cross-tenant listing of every agent ever claimed on this instance, with totals. Requires the operator's admin_secret — this is a portfolio-wide view, not a per-agent report (use ledger_report for that — it requires that agent's agent_secret or its workspace_key).
Esquema de entrada
{
"type": "object",
"properties": {
"admin_secret": {
"default": "",
"type": "string",
"description": "operator admin secret (not the same as an agent_secret)"
}
},
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟡ledger_start
Get a FREE AgentLedger workspace with no credential and no arguments — the MCP equivalent of opening POST /start in a browser. Call this FIRST if you have no credentials yet. Every other tool here (ledger_track, ledger_set_budget, ledger_report, ledger_alerts) needs a workspace_key or an agent_secret, so a caller arriving with neither must start here or it has nowhere to go. Takes NO arguments on purpose: the goal is zero friction. It returns a `workspace_key` (shown exactly once — it cannot be re-revealed, so store it before continuing) which you then send as `workspace_key` on your first ledger_track for a NEW agent_id. That first write returns the agent's own `agent_secret`, which authenticates every write after it. The free tier includes every rail, enforced budget caps, alerts, reports and the MCP server, capped at 3 agents per workspace. Minting is rate-limited per caller IP, the same limit the human door uses. Prefer to pay? POST /v1/billing/x402 with a wallet-signed payment needs no human and buys 24h of Pro (unlimited agents).
Esquema de entrada
{
"type": "object",
"properties": {},
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢ledger_api_docs(topic)
Self-serve documentation for AgentLedger — quickstart, MCP tools, REST endpoints, budget caps, error codes, and idempotency usage, as markdown.
Esquema de entrada
{
"type": "object",
"properties": {
"topic": {
"default": "",
"type": "string",
"description": "\"quickstart\" | \"mcp\" | \"rest\" | \"budget\" | \"errors\" | \"idempotency\" | \"all\"\n (default \"\" == \"all\"). Unknown topics fall back to the full docs."
}
},
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢ledger_examples(pattern)
Complete, runnable Python recipe for a common AgentLedger integration pattern.
Esquema de entrada
{
"type": "object",
"properties": {
"pattern": {
"type": "string",
"description": "\"python_tracking\" | \"budget_enforcement\" | \"weekly_report\" |\n \"retry_safe_writes\""
}
},
"required": [
"pattern"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢skills_list_tool
List this product's skills. Each entry carries the SKILL.md URI, its name and description, verbatim frontmatter, and a per-file sha256 manifest. Read a body with `read_skill`.
Esquema de entrada
{
"type": "object",
"properties": {},
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}🟢read_skill(uri)
Read a product skill file by its skill:// URI.
Esquema de entrada
{
"type": "object",
"properties": {
"uri": {
"type": "string",
"description": "e.g. skill://<product>/<skill-name>/SKILL.md\n Get valid URIs from `skills_list_tool`."
}
},
"required": [
"uri"
],
"additionalProperties": false
}Esquema de salida
{
"type": "object",
"additionalProperties": true
}Comunidad
Evidencia