AgentRaaS wrap

io.github.agentraasPublished by GitHub account agentraasv0.16.0Updated Oct 31, 2026

Wraps any MCP server: identical write-tool calls run once, and every tool call is audit-logged.

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Overview

AI-generated overview

Wraps any MCP server so identical write-tool calls run only once within a dedup window, and every tool call is appended to an audit log.

What you can do
  • Wrap an existing MCP server command so identical calls to write tools return the first result instead of running again
  • Keep read-only lookups fresh, with dedup decided by readOnlyHint annotations or tool names, and override per tool
  • Skip caching failed calls so a retry runs for real, and mark deduplicated results in the response metadata
  • Record every tool call to a local audit log file
  • Scan MCP server configs to list tools that move money, delete data, run code or send messages, without calling them
When to use it
Useful when an agent retries or loops and could send the same email, open the same issue or repeat another side-effecting tool call twice. Also worth adding before shipping an agent that uses third-party MCP servers, to see which tools can act on the real world.
Requirements
Runs locally over stdio as a Python package installed with uvx or pip; it is placed in front of another MCP server's command. No accounts, API keys or environment variables are declared for the wrap mode. State and logs are written under the user's home directory by default.
Before you install
It sits in front of another server and sees every tool call, which it writes to a local audit log file. Dedup is heuristic: tools not recognized as read-only are treated as writes, so a repeated call may return a cached result for up to the default 10-minute window. The scan command starts the MCP servers in the configs it reads, so only scan configs you trust.

Installation

In SourceWeft

  1. Open AgentRaaS wrap in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

agentraas (Python SDK)

The reliability layer for what AI agents do. Every action your agent takes (a charge, an email, a CRM update, a tool call) runs once even when it is retried, can be checked against rules before it runs, and is recorded. This package brings that to your code:

  • @exactly_once and protect_tool (LangChain/LangGraph, CrewAI): a retry, yours, your framework's or a flaky network's, never becomes a duplicate charge or message. No server needed.
  • agentraas wrap: the same for any MCP server's write tools.
  • agentraas scan: lists which tools in your MCP servers can move money, delete data, run code or send messages, without calling any of them.
  • agentraas chaos: finds the calls in your agent that would double up under retries, before production does.
  • Client: points your calls at an AgentRaaS server for action policies, human approval, spend caps, circuit breaking and an audit trail.

Works against any AgentRaaS deployment: self-hosted (./install.sh, free and unlimited on every tier) or AgentRaaS Cloud.

Install

bash
pip install agentraas

Library mode: no server needed

Wrap any function that has a side effect (charging a card, sending an email, creating a CRM record) so retries and concurrent duplicates run it exactly once. Nothing to deploy: state lives in a local SQLite file by default, or in your own Redis.

python
from agentraas.local import exactly_once, RedisStore
@exactly_once()                                   # SQLite file, one machinedef charge(customer, amount):    return stripe.Charge.create(customer=customer, amount=amount).id
charge("cus_1", 4200)   # runs for realcharge("cus_1", 4200)   # retry: returns the cached id, no second charge
# Across machines, with your own idempotency key and window:@exactly_once(store=RedisStore("redis://localhost:6379/0"),              key=lambda order: order["id"], ttl=3600)async def ship(order):    ...
  • If the function raises, nothing is cached and a retry runs it again. That includes the case where the provider did the work but the response was lost, so give the function an idempotency_key parameter and send it to the provider (e.g. Stripe's Idempotency-Key header). The decorator fills it with the same value on every retry:

    python
    @exactly_once()def charge(customer, amount, idempotency_key=None):    return stripe.Charge.create(customer=customer, amount=amount,                                idempotency_key=idempotency_key).id
  • A duplicate that arrives while the first call is still running waits for its result (up to wait=30 seconds, then InFlightError).

  • Results must be JSON-serializable (return ids or dicts, not SDK objects).

  • RedisStore needs pip install redis.

When you want a dashboard, audit trail, human approval or circuit breaking on top, point the same calls at an AgentRaaS server with the Client below.

LangChain / LangGraph: exactly-once tool calls

pip install "agentraas[langchain]", then wrap the tools that have side effects. Works with LangChain agents, create_react_agent and ToolNode.

python
from agentraas.langchain import protect_tool
tools = [protect_tool(charge_card), protect_tool(send_email), search]agent = create_react_agent(model, tools)

When the model calls a protected tool again with the same arguments, or the graph re-runs the tool node after a crash or retry, the stored result comes back instead of a second charge. Takes the same store=, key= and ttl= options as @exactly_once above (e.g. store=RedisStore(...) for several workers, key=lambda order_id, **_: order_id). Tool results must be JSON-serializable.

CrewAI: exactly-once tool calls

pip install "agentraas[crewai]" (CrewAI needs Python 3.10+), then wrap the tools that have side effects, either BaseTool subclasses or @tool functions:

python
from agentraas.crewai import protect_tool
agent = Agent(role="Billing", goal="...", backstory="...",              tools=[protect_tool(ChargeCardTool()), protect_tool(send_email)])

When the agent calls a protected tool again with the same arguments, or a crew is kicked off again after a crash, the stored result comes back instead of a second charge. Same store=, key= and ttl= options as above. The original tool object is left unchanged.

MCP wrap: exactly-once tool calls for any MCP server

Put agentraas wrap -- in front of an MCP server's command. Everything passes through unchanged, except that an identical call to a write tool (same tool, same arguments) inside the dedup window gets the first call's result back instead of running again. An agent that retries or loops can't send the same email or open the same issue twice. Every tool call is appended to an audit log.

Claude Desktop / Cursor config:

json
{  "mcpServers": {    "github": {      "command": "uvx",      "args": ["agentraas", "wrap", "--", "npx", "-y", "@modelcontextprotocol/server-github"]    }  }}
  • Read-only tools are never deduplicated, so lookups stay fresh. The server's readOnlyHint annotation decides, falling back to names like get_*, list_*, search_*. Override with --dedupe TOOL / --no-dedupe TOOL.
  • A failed call (JSON-RPC error or isError: true) is not cached, so a retry runs for real.
  • Default window: 10 minutes (--ttl 600). State lives in ~/.agentraas/mcp-dedup.db, the log in ~/.agentraas/mcp-audit.jsonl (--db, --log).
  • A deduplicated result carries _meta: {"agentraas/deduplicated": true}.

MCP safety scan: which tools can act on the real world

bash
agentraas scan                                    # every server in your Claude Desktop, Cursor, Claude Code configsagentraas scan -- npx -y @modelcontextprotocol/server-githubagentraas scan --config .mcp.json --fail-on high  # CI: exit 1 on a high-risk tool

Starts each stdio server the way your client does, sends only initialize and tools/list, and sorts the tools: moves money, deletes, runs code, sends (high), writes (medium), reads (low), from their readOnlyHint/destructiveHint annotations and the words in their names. Only scan configs you trust: it runs their commands. --json for machine-readable output. https://agentraas.io/mcp-scan

GitHub Actions:

yaml
- uses: agentraas/agentraas/src/scan-action@main  with:    config: .mcp.json   # or command: "npx -y @modelcontextprotocol/server-github"; fail-on: high | medium | none

Chaos tester: find the calls your agent would run twice

agentraas-chaos sits between your code and an API. The first time each distinct write request (POST/PUT/PATCH/DELETE) arrives, it lets the request execute and then drops the response, the network failure that turns a retry into a double charge. Then it reports every action that executed more than once.

bash
pip install agentraas
# Safe: a built-in mock answers every call, nothing real is touchedagentraas-chaos --mock -- python my_agent.py
# Against a real API: use TEST-mode keysagentraas-chaos --upstream https://api.stripe.com -- pytest

Your command gets AGENTRAAS_CHAOS_URL (e.g. http://127.0.0.1:8787); use it as the API base URL. Without a command it runs until Ctrl-C, so you can point an n8n workflow or any other tool at it by hand.

agentraas-chaos: 6 write requests, 3 responses dropped after execution
  DUPLICATES: 1 action(s) executed more than once
    2x  POST /v1/charges  (body sha256 623f14d1b00d)  ...  Protected by an idempotency key: 2 retries

It exits with code 1 when it finds a duplicate, so it can fail CI. --fault error-after-commit returns a 502 instead of dropping the connection. A retry that repeats an Idempotency-Key it has already seen is counted as protected, not executed again.

In GitHub Actions:

yaml
- uses: actions/setup-python@v5  with: { python-version: "3.12" }- uses: agentraas/agentraas/src/chaos-action@main  with:    run: python my_agent.py

Keep rules in Git: agentraas apply

Describe a server's dedup rules, validation rules, action policies and spend caps in YAML, review them like code, and apply them from CI:

bash
pip install "agentraas[apply]"
yaml
# agentraas.yamlapiVersion: agentraas.io/v1alpha1kind: DedupRulemetadata: {name: charge-once, org: org_acme}spec: {service: stripe, action: charges.create, fields: [customer, amount], ttlSeconds: 300}---apiVersion: agentraas.io/v1alpha1kind: SpendCapmetadata: {org: org_acme}spec: {service: stripe, action: refunds.create, window: day, maxCalls: 100, onExceed: block}
bash
export AGENTRAAS_URL=https://agentraas.example.com [email protected] AGENTRAAS_PASSWORD=...agentraas apply -f agentraas.yaml --dry-run   # print the planagentraas apply -f agentraas.yaml             # create what's missing, replace what changedagentraas apply -f agentraas.yaml --prune     # also delete rules the file doesn't list

Kinds: DedupRule, ValidationRule, ActionPolicy, SpendCap. Spec keys are the API's fields in camelCase. Running it twice changes nothing.

Local tunnel: test webhooks against your laptop

agentraas tunnel prints a public URL and replays every request sent to it against a local port, so you can point Stripe, GitHub or n8n webhooks at code you haven't deployed. Needs a free AgentRaaS account (an agent API key).

bash
pip install "agentraas[tunnel]"agentraas tunnel --port 3000 --org org_acme --agent agent_1 --key ar_live_...

One tunnel per org, 2-hour sessions, 30-second local response timeout.

Send one action from the shell: agentraas call

Every command also runs under the short name agtrs. call sends one action through an AgentRaaS server and prints the answer as JSON: the same dedup, policies, approvals and audit as the Client. Handy for scripts and for checking a rule by hand.

bash
export AGENTRAAS_KEY=ar_live_... AGENTRAAS_ORG=org_acme AGENTRAAS_AGENT=agent_1export AGENTRAAS_URL=https://agentraas.io      # default http://localhost:13000agtrs call stripe charge.create '{"amount": 4999, "currency": "usd"}'echo '{"text": "hi"}' | agtrs call slack message.post -

--key, --org, --agent, --url and --idempotency-key override the environment. A rejected call prints the error and its hints and exits 1.

Approve held calls from the shell

The same list as the dashboard's Waiting for approval, for any org you can write to. Logs in like apply (AGENTRAAS_EMAIL / AGENTRAAS_PASSWORD against AGENTRAAS_URL, default https://agentraas.io).

bash
agtrs approvals                  # req id, service, action, agent, payloadagtrs approve req_abc123         # runs the call; asks first (--yes to skip)agtrs deny req_abc123

approve exits 1 if the call ran and failed (it is then in Failed requests). Without a terminal it refuses unless --yes is passed, so a script never approves by accident.

Read the audit log from the shell

Every call in the orgs you belong to, newest first, with the same login as approvals:

bash
agtrs audit                      # last 50: time, status, service action, agent, org, duration, req id, erroragtrs audit -n 200 --json        # adds run/step ids, dedup hash, redacted payload preview (max 1,000)agtrs audit --csv > audit.csv    # the dashboard's CSV export (newest 10,000)

Failed calls from the shell

Calls that failed and were kept (the dashboard's Failed requests), with the same login as approvals:

bash
agtrs dlq                        # id, time, service action, agent, org, req id, erroragtrs dlq replay 42              # sends the call again with the same idempotency key; asks first (--yes to skip)agtrs dlq dismiss 42             # drop it without sending

replay exits 1 if the service fails again; the entry stays in the list.

Move dashboard rules into Git

agtrs rules prints the rules already on the server as a file apply accepts, so applying it right away changes nothing:

bash
agtrs rules --org org_acme > agentraas.yamlagtrs apply -f agentraas.yaml --dry-run   # no changes

Quickstart

  1. Connect an agent from your AgentRaaS dashboard (+ Connect Agent) — this gives you an agentraas_key, plus your org_id and agent_id.
  2. Add credentials for the service you're calling (Credentials panel) — AgentRaaS forwards to the real API using those, you never pass a raw upstream API key through this SDK.
python
import agentraas
client = agentraas.Client(    agentraas_key="ar_live_...",    org_id="acme-corp",    agent_id="billing-bot",    base_url="http://localhost:13000",  # or your Cloud/self-hosted URL)
result = client.call("stripe", "charge.create", {"amount": 5000, "currency": "usd"})

Or with dot-notation sugar:

python
stripe = client.service("stripe")result = stripe.charge.create({"amount": 5000, "currency": "usd"})

Calling a Custom Action you've registered:

python
result = client.custom("my-internal-webhook", {"foo": "bar"})

Why org_id / agent_id matter

Omit them and every untagged SDK caller shares one unenforced identity server-side — your per-agent rate limit and audit trail won't tell your traffic apart from anyone else's. Set them once you've connected an agent from the dashboard; it takes two extra kwargs.

Retries are safe

AgentRaaS claims an atomic dedup slot server-side before forwarding anything. If client.call(...) raises because of a timeout or a dropped connection, calling it again with the same payload is safe — it either completes normally or returns the cached result from the call that actually went through. This SDK doesn't retry automatically; your own retry logic (or your agent framework's) can be as aggressive as you want.

One case is different: if the provider doesn't answer AgentRaaS in time, you get a 504 with "outcome": "unknown", and identical calls get a 409 until it's resolved. Retrying won't run it, on purpose, since it may already have gone through. Check with the provider, then replay or dismiss it from Failed Requests in the dashboard (steps). If you're sure it did not run, resend it as a new action with your own key:

python
client.call("stripe", "charge.create", payload, idempotency_key="order-1042-retry-1")

Record locks

When two agents change the same customer or order at once, the second gets a 409 (how it works). To wait for the record instead (up to 5 seconds, first come first served), or to lock an id of your own choosing:

python
client.call("stripe", "refund.create", payload, lock_wait_ms=2000)client.call("custom", "update_order", payload, resource_id="order-1042")

Record and replay

Run an agent once against the real providers, then replay it (in a test, in CI, after a prompt change) without calling them again:

python
recorder = Client(agentraas_key, org_id, agent_id, record="refund-flow")# ... run the agent with recorder ...
replayer = Client(agentraas_key, org_id, agent_id, replay="refund-flow", run_id="ci-42")# each call is answered from the recording, in order; nothing reaches the provider

Each replayed answer carries replay: {recording, position, payload_matches}; a call the recording doesn't have raises a 404. A new run_id starts from the top. Details: agentraas.io/docs#record-replay.

Error handling

python
from agentraas import AgentRaaSError
try:    client.call("stripe", "charge.create", {"amount": 5000, "currency": "usd"})except AgentRaaSError as err:    print(err.status_code, err.req_id, str(err))    if err.status_code == 504:        pass  # outcome unknown: don't retry blindly, resolve it first

A payload that fails a validation rule raises a 422 with every failing field in err.validation_errors (field, rule, message, hint). Nothing was sent, and str(err) lists each hint, so an agent shown the error can fix them all in one retry:

text
[422] amount must be number, got string (reqId=...)- amount: Send "amount" as a JSON number: 49.99, without quotes.- currency: Send "usd" (exact spelling) in "currency".Nothing was sent. Fix every field listed in validation_errors, following each hint, and send the call again.

License

MIT — see LICENSE. (The AgentRaaS server core is MIT too, its Team/Enterprise features source-available; see the main repo.)

Source: src/sdk/README.md at commit 66c74ab

Tools

0
SourceWeft started this package once in an isolated sandbox, without credentials, to list its tools. That failed: the server did not start.

Version history

6
  1. v0.16.0LatestOct 31, 2026
  2. v0.15.1Oct 30, 2026
  3. v0.15.0Oct 29, 2026
  4. v0.14.0Oct 22, 2026
  5. v0.13.0Oct 22, 2026
  6. v0.12.1Oct 21, 2026

Score

40% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.