bastiongate
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@bastiongateset up the security gateway with policy.yaml and log traffic to gate.jsonl"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
bastiongate
MCP security gateway. An inline proxy that sits between an AI agent and its MCP servers and enforces security on every call:
scans
tools/listand drops tools whose definitions carry prompt injection or hidden unicode (via bastionsupply)enforces a tool allow/deny policy — the agent can only call what you permit
scans tool-call results and blocks any that carry indirect prompt injection before the agent ever reads them
logs every message as a JSONL trace for forensics
The runtime-enforcement leg of the bastion family:
tool | job |
bastiongate | gate — enforce security inline on live MCP traffic |
scan an MCP server before you trust it | |
prevent — firewall around a running agent | |
attack — pentest your agent with injections | |
investigate — forensics on an agent trace |
Install
pip install bastiongateway(The PyPI distribution is bastiongateway; the import package and bastiongate
CLI keep that name.)
Related MCP server: SafeNode MCP Gateway
Use
The gate is an MCP server to your agent, and a client to the real one. Point
your MCP client's command at the gate and put the real server after --:
// mcp.json
{
"mcpServers": {
"docs": {
"command": "bastiongate",
"args": ["run", "--policy", "policy.yaml", "--log", "gate.jsonl",
"--", "npx", "-y", "@some/mcp-server"]
}
}
}Everything the agent sends flows through the gate to the server and back, with the checks applied in between.
Policy
Drop in the same YAML bastionsupply harden emits:
default: deny
allow:
- get_weather
- search_docs
deny:
- run_command
# behavior knobs (defaults shown)
scan_tools: true # scan tools/list
on_poisoned_tool: block # drop poisoned tools from the listing
scan_results: true # scan tool-call results
on_injected_result: block # block results carrying injection
scrub_args: true # scan tool-call arguments for secrets/PII
on_pii_arg: redact # redact | block | warn
scrub_results: false # scan tool-call RESULTS for secrets/PII (opt-in)
on_pii_result: redact # redact | block | warn
result_inspector: static # static | agentbastion (deeper inspection)
inspector_fail: closed # closed | open (behavior if the inspector errors)
inspector_judge: false # agentbastion: also use the Anthropic LLM judge
inspector_semantic: false # agentbastion: also use the semantic detector
# per-tool overrides — any of the knobs above, scoped to one tool
tools:
send_email:
scrub_args: false # the recipient email is the point; don't redact it
fetch:
on_injected_result: warnSo the pipeline is: scan the server with bastionsupply → harden a policy →
run it live behind bastiongate.
Argument PII/secret scrub
On every tools/call the gate scans the arguments the agent is about to send
and, by default, redacts secrets/PII ([REDACTED:<kind>]) before they reach
the tool — API keys, AWS/GitHub/Slack tokens, private keys, JWTs, emails, SSNs,
and Luhn-valid card numbers. on_pii_arg: block refuses the call instead;
warn only logs. Only the kind is ever logged, never the value.
HTTP transport
For MCP Streamable-HTTP servers, run the gate as an HTTP proxy instead:
bastiongate run-http --upstream http://127.0.0.1:8000/mcp --port 9000 --policy policy.yamlPoint your client at http://127.0.0.1:9000/mcp. JSON and SSE responses are
both gated. Binds 127.0.0.1 by default. Add --auth-key KEY (or env
BASTIONGATE_PROXY_KEY) to require an X-Bastiongate-Key header on every
request; the key is compared in constant time and never forwarded upstream.
GET /__bastiongate/metrics returns a JSON counter of what the gate has caught
(blocks by type, tools dropped, pending/session counts). It's auth-gated when a
key is set. In stdio mode the same counters are written to the trace at exit.
Deeper result inspection (agentbastion)
result_inspector: agentbastion swaps the static signature scan for
agentbastion's inbound Firewall,
composed of up to three tiers: heuristics (always), the semantic detector
(inspector_semantic: true + BASTIONGATE_EMBED_URL), and the Anthropic LLM
judge (inspector_judge: true + ANTHROPIC_API_KEY).
pip install "bastiongateway[agentbastion]" # heuristic
pip install "bastiongateway[agentbastion-local]" # + semantic (local model, no egress)
pip install "bastiongateway[agentbastion-semantic]" # + semantic (remote embed endpoint)
pip install "bastiongateway[agentbastion-judge]" # + LLM judgeThe semantic detector needs an embedder, chosen by env:
BASTIONGATE_EMBED_MODEL— a local sentence-transformers model (e.g.all-MiniLM-L6-v2). Result text never leaves the process. Preferred.BASTIONGATE_EMBED_URL— a self-hosted embeddings endpoint (result text is POSTed to it).
The model is loaded and its templates embedded at gate startup (not on the
first result), bounded by BASTIONGATE_EMBED_INIT_TIMEOUT (default 120s); set
BASTIONGATE_EMBED_WARM=0 to defer. For air-gapped hosts, pre-cache the model
and set HF_HUB_OFFLINE=1 — the first uncached load fetches from HuggingFace.
Try it
bastiongate run --log gate.jsonl -- python examples/echo_server.pyThe example server offers a poisoned tool and an injected result; the gate drops
the first and blocks the second. Watch gate.jsonl.
Library
from bastiongate import Gate, GatePolicy
gate = Gate(GatePolicy(deny={"run_command"}))
forward, reply = gate.handle_client_msg(msg) # agent -> server
out = gate.handle_server_msg(response) # server -> agentGate is a pure message transform — easy to embed or test.
Security notes & limitations
Argument redaction can alter legitimate calls.
on_pii_arg: redactrewrites anything that looks like PII — including a recipient email asend_emailtool actually needs. Scope it with a per-toolscrub_args: falseoron_pii_arg: warn(seetools:above). Scrubbing is best-effort DLP: base64-encoded or field-split secrets can slip through.Result scrub covers both
textcontent blocks andstructuredContent, and the injection scan readsstructuredContenttoo (not only text blocks).The HTTP listener throttles an IP after repeated auth failures (
429), and correlation state is bounded per session (LRU eviction) with an idle TTL.The HTTP proxy adds no auth of its own. It binds
127.0.0.1by default and passes the client'sAuthorizationheader through to the upstream. Do not bind a public interface without an auth layer in front.The HTTP proxy does not follow upstream redirects and only speaks
http/https— a malicious upstream cannot bounce it tofile://or an internal address.JSON-RPC batch arrays on the request side are passed through un-gated (responses are still scanned); single messages — the normal case — are fully gated. Chunked request bodies (no
Content-Length) are not supported.inspector_fail: closed(default) blocks a result if the inspector errors or times out. The LLM judge runs on every result (cost + latency); it has aBASTIONGATE_JUDGE_TIMEOUT(default 10s).
MIT.
This server cannot be deployed
Maintenance
Related MCP Connectors
Security & DLP proxy for MCP: tool-poisoning scans, PII redaction on tool args/results. Beta.
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MCP enforcement layer that intercepts AI agent actions and blocks rule violations before execution.
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MCP gateway with runtime security policy, tool-call-level control, and audit of agent actions.
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