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Read-only MCP server for coding-agent traces, alerts, costs, usage, and budget health.
About
Read-only MCP server for coding-agent traces, alerts, costs, usage, and budget health.
Security Report
AgentGuard is a well-designed runtime control SDK with strong security practices. The codebase demonstrates proper input validation, secure credential handling (no hardcoded secrets), and appropriate permission scoping. Minor code quality observations exist around exception handling breadth, but these do not constitute security vulnerabilities. The MCP server component is read-only and appropriately scoped. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 2 high severity). Package verification found 1 issue.
4 files analyzed · 6 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: AGENTGUARD_API_KEY
Environment variable: AGENTGUARD_URL
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-bmdhodl-agentguard47": {
"env": {
"AGENTGUARD_URL": "your-agentguard-url-here",
"AGENTGUARD_API_KEY": "your-agentguard-api-key-here"
},
"args": [
"-y",
"@agentguard47/mcp-server"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
AgentGuard
Stop runaway agents with runtime checks in Python.
AgentGuard checks budgets, repeated tool calls, retries, and elapsed time in instrumented Python code. Guards raise exceptions so your application can stop the next operation. The base SDK has no runtime dependencies and needs no account.
Names: this repository is agent47, the PyPI package is agentguard47,
and the Python import is agentguard. Requires Python 3.9 or newer.
Getting started
Install in a virtual environment, then run the offline checks:
python -m pip install agentguard47
agentguard doctor
agentguard demo
doctor checks the installation and local trace writing. demo exercises
budget, loop, and retry stops without provider keys or network access. Follow
the trace path printed by the command to inspect its output.
agentguard demo --feedback prints a local redacted report; nothing is sent.
agentguard receipt agentguard_demo_traces.jsonl prints a receipt of each stop
with the trace's SHA-256 drawn as a barcode. Add --format markdown to paste it
into a PR or issue. The hash identifies the trace file; it is not a signature.
Guard a Claude Code session
agentguard hook claude-code --install --write
This installs a Claude Code hook that refuses the third identical tool call in
a row and a call that already failed twice. Refusals go to
.agentguard/claude-code/trace.jsonl. It checks tool calls, not tokens or
subscription quota. See the Claude Code hook guide.
Guard a script without editing it
agentguard run --budget-usd 5 agent.py
This patches the OpenAI and Anthropic clients, then runs agent.py in the same
interpreter. Settings come from flags, then environment variables, then
.agentguard.json. A guard stop exits 1. Every run ends with the trace path on
stderr, ready for agentguard receipt. agentguard run python -m mypkg works too. The bounds are
the same as patching the client yourself; see
enforcement boundary.
Stop before a third call
Save this as budget_demo.py and run python budget_demo.py. It makes no
network requests.
from agentguard import BudgetExceeded, BudgetGuard
budget = BudgetGuard(max_calls=2)
completed = 0
for _ in range(3):
try:
budget.check() # Check before the operation.
# Put your provider or tool call here.
completed += 1
budget.consume(calls=1) # Record the completed operation.
except BudgetExceeded:
print(f"Stopped before call {completed + 1}")
assert completed == 2
Expected output: Stopped before call 3.
Connect a provider
Install the provider's client separately. For OpenAI:
python -m pip install openai
from agentguard import BudgetGuard, JsonlFileSink, Tracer, patch_openai
budget = BudgetGuard(max_cost_usd=5.00)
tracer = Tracer(
service="my-agent",
sink=JsonlFileSink(".agentguard/traces.jsonl"),
)
patch_openai(tracer, budget_guard=budget)
# Make your OpenAI chat.completions.create or responses.create calls after this setup.
The patch checks recorded usage before dispatch and records response usage
afterward, including streamed calls once the final usage arrives. A response
can exceed the remaining cost or token allowance. Concurrent requests do not
reserve capacity. Chat Completions streams request include_usage unless the
caller already set it.
The OpenAI Agents SDK runs on responses.create, so agentguard.init() before
the Runner puts every model call under the budget
(example). Hosted tools and
background=True responses are not covered. See the getting started guide
for setup, traces, and framework starters.
How enforcement works
flowchart TD
accTitle: AgentGuard operation checks
accDescr: Check a limit before an operation, then record usage.
A[Instrumented operation] --> B{Guard check}
B -->|Limit reached| C[Raise exception]
B -->|Allowed| D[Run operation]
D --> E[Record usage and trace]
E --> A
Text equivalent: check before an operation, run it if allowed, then record usage. A guard exception returns control to your application's error handler.
| Guard | Checks | Raises |
|---|---|---|
BudgetGuard | Recorded calls, tokens, or estimated cost | BudgetExceeded |
LoopGuard | Repeated tool calls | LoopDetected |
FuzzyLoopGuard | Tool frequency and alternating patterns | LoopDetected |
RetryGuard | Retries per tool | RetryLimitExceeded |
TimeoutGuard | Elapsed time when checked | TimeoutExceeded |
RateLimitGuard | Calls within a sliding minute | BudgetExceeded |
X402SpendGuard | Payment amounts before the payment callback | BudgetExceeded |
For task budgets, use BudgetGuard.goal(...). For signatures and defaults,
read the guard source and
public exports.
Limits and security
- Guards cover operations you instrument. Installing the package does not intercept every action in Cursor, Claude Code, or another agent.
- A guard is not a sandbox or permission system. A permitted operation can still be destructive.
- Timeout checks do not interrupt an already blocked function or cancel an agent running on a provider's server.
- Cost estimates are not invoices. Supply reported cost or use strict cost resolution when an estimate is insufficient.
- Recorded-budget preflight refuses the next instrumented call when stored usage is already at a cap. It does not reserve concurrent in-flight requests, predict the next response, or cap a provider subscription. See the enforcement boundary.
- The base SDK uses the standard library. Optional framework extras install third-party dependencies and need their own security review.
- The optional
[crewai]extra pulls ChromaDB. The 2026-09-12 audit found four unresolved advisories, including PYSEC-2026-311 / CVE-2026-45829. Review that exposure before installing the extra. Base SDK installs do not include ChromaDB. - Trace content can contain application data. Review it before sharing or configuring a remote sink.
See security reporting, the dated dependency audit, and release notes. Audit results describe their recorded date, not a permanent clean bill of health.
Local traces and optional hosted ingest
The SDK is the free local proof path. Start local. Add hosted ingest only when you need retained history, alerts, team visibility, spend trends, hosted decision history, or dashboard-managed remote kill signals.
Local guards remain authoritative. HttpSink mirrors trace and decision events;
it does not execute remote kill signals by itself. See the
dashboard contract before configuring it.
Local use has no hosted event quota, retention period, or API-key allocation.
Network egress requires an integration you configure, such as HttpSink or
an OpenTelemetry exporter.
Nothing in the local SDK phones home. The AgentGuard website describes the optional hosted service.
Documentation
| You want to | Start here |
|---|---|
| See which paths actually stop a call | Enforcement boundary |
| Install and trace a first run | Getting started |
| Find guides and source references | Documentation index |
| Try a runnable example | Examples |
| Connect LangChain, LangGraph, or CrewAI | Integration guides |
| Inspect hosted data through MCP | Read-only TypeScript MCP server |
| Use local budget tools through MCP | Python budget MCP server |
| Navigate with an AI assistant | AI documentation index |
| Contribute a fix | Contributing |
| Check what changed | Changelog |
Help and maintenance
Maintained by Patrick Hughes. Report a bug with the package version, a minimal reproduction, and the expected result. Report vulnerabilities through SECURITY.md.
The source metadata defines the branch version. The PyPI badge links to the published version. Documentation examples and local links are tested in CI. The PyPI README is generated from this README and the changelog.
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