Prism MCP for Python
Consuming Model Context Protocol servers as Prism tools, across an explicit trust
boundary. The Python port of
particle-academy/prism-mcp.
Zero runtime dependencies. Python 3.10+.
pip install prism-ai-mcp
from prism_mcp import Client, TrustPolicy
docs = Client(
"docs",
my_transport,
trust=TrustPolicy.allowing(["search"], pins={"search": "sha256:3f1c…"}),
)
tools = docs.list_tools()
result = docs.call_tool(tools[0], {"query": "rate limits"})
print(result.text)
my_transport is a callable that sends a TransportRequest (method, params,
headers) to the server and returns the decoded result. The package opens no
connections itself.
Trust
A tool list is not data the model summarises; it is instructions the model follows. So nothing is offered until you say what you trust.
TrustPolicy.undeclared()is the default.list_tools()raisesserver_not_trustedinstead of returning the server's tools.TrustPolicy.allowing([...])offers only the named tools.allowing([])is a declaration too, and offers nothing.TrustPolicy.allowing_every_tool()offers every tool, including ones the server adds later.- Pins. Pass
pins={name: digest}.ToolDefinition.digest()covers the tool's name, title, description and input schema, so a server that rewrites a description after you trusted it is refused withtool_definition_changed.
A gate callable (server, tool, arguments) -> bool is asked before every
call; returning False raises tool_denied. The default allows every call that
trust admitted, and deny_all refuses them all.
Results
Every result passes through a ResultGuard before it reaches you:
- A result over
max_bytes(65,536 by default) raisesresult_too_largeinstead of being truncated. - The text is wrapped in an
<untrusted-tool-output>tag with a random id per result, so the server's output cannot close the wrapper. - A
filtercallable(server, tool, text) -> textruns before framing, if you pass one.
The wrapper makes a prompt injection harder. It does not make one impossible, and the guard does not scan the text for injection strings.
Mirrored parameters
A tool's schema can mark an argument with x-mcp-header, which copies the
model's value into an Mcp-Param-* request header. A tool whose annotations
break the rules (an invalid header name, two arguments mirrored to the same
header) is left out of list_tools() rather than repaired.
Protocol
The client speaks MCP 2026-07-28, the stateless revision. Earlier revisions
open with an initialize handshake and a session, which this client does not
implement. is_stateless_protocol(version) tells the two apart.
Errors
Every failure is an McpError with a stable code: server_not_trusted,
tool_definition_changed, tool_denied, result_too_large,
mirrored_parameter_refused, unsupported_protocol_version,
protocol_failure, tool_call_failed, server_not_configured.
Parity
prism-parity's mcp-tool-digest corpus pins tool digests against the PHP
reference and the TypeScript port, so a pin computed in one language holds in
the others.
One case is not in that corpus: a schema containing an integral float such as
1.0 digests differently here than in PHP and TypeScript. For such a tool,
compute the pin in Python.
License
MIT. See LICENSE.
Release files for prism-ai-mcp 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| prism_ai_mcp-0.1.0.tar.gz | 11.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| prism_ai_mcp-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.8 kB
Release files / prism_ai_mcp-0.1.0.tar.gz
| Download URL | prism_ai_mcp-0.1.0.tar.gz |
|---|---|
| Size | 11.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / prism_ai_mcp-0.1.0-py3-none-any.whl
| Download URL | prism_ai_mcp-0.1.0-py3-none-any.whl |
|---|---|
| Size | 12.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
241825953cb6b505d0c827eec1563699998adf31c8060f049e774269e6f9549c
|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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