io.github.loopg/pramana-mcp
PYPI · PRAMANA-MCP
Read your recorded AI agent runs, and what changed when you swapped a model or prompt.
Available components
Last scanned (3 hours ago)
Scores higher than 74% of PyPI servers
Category AI and Machine Learning
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 1 of 32 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 37 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability68
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 265 tokens (~53/item across 5 items; 5 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management70
- Stability observed for 21 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 5 Nov 26 +16
- Malware scan: unverified → pass ▲ security
- 4 Nov 26 −15
- Malware scan: pass → unverified ▼ security
- 3 Nov 26 +10
- Malware scan: unverified → pass ▲ security
- Stability: pass → 0.63 functional
- 30 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 29 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 28 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- Stability: 0.97 → pass security
- 27 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 25 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Analysed pypi/pramana-mcp@0.1.3
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
| Reason | No attestation published |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 32 packages
| Packages resolved | 32 |
|---|---|
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
get_model_diff ~46
Get the findings of one comparison run: which decisions changed behaviourally, which were cosmetic, and which runs halted.
| Name | Type | Req | Description |
|---|---|---|---|
| diff_id | string | yes | – |
| trace_id | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_trace ~36
Get one recorded agent run: its steps, model calls, tool calls with arguments, and outcome.
| Name | Type | Req | Description |
|---|---|---|---|
| trace_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_model_diffs ~37
List comparison runs that checked a prompt or model change against recorded production runs.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| since | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_traces ~50
List recorded AI agent runs (traces) captured by Pramana, optionally filtered by agent, status or time range.
| Name | Type | Req | Description |
|---|---|---|---|
| agent | – | – | – |
| limit | integer | – | – |
| since | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
verify_bundle ~42
Verify a Pramana signed evidence bundle offline, with no account and no network access.
| Name | Type | Req | Description |
|---|---|---|---|
| bundle_path | string | yes | – |
| public_key_path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the io.github.loopg/pramana-mcp server?
io.github.loopg/pramana-mcp runs locally as a PyPI package, launched with uvx pramana-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · pramana-mcp
claude mcp add loopg-pramana-mcp -- uvx pramana-mcp
What is the io.github.loopg/pramana-mcp server?
io.github.loopg/pramana-mcp is listed in the public MCP registry as io.github.loopg/pramana-mcp. Read your recorded AI agent runs, and what changed when you swapped a model or prompt. This page covers its PyPI package (pramana-mcp).
Is the io.github.loopg/pramana-mcp server safe to use?
io.github.loopg/pramana-mcp scores 77 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.loopg/pramana-mcp server expose?
io.github.loopg/pramana-mcp exposes 5 tools: list_traces, get_trace, list_model_diffs, get_model_diff, verify_bundle. Their descriptions and schemas cost roughly 211 tokens of context every time the server is loaded.
Is the io.github.loopg/pramana-mcp server still maintained?
io.github.loopg/pramana-mcp is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.loopg/pramana-mcp server under?
io.github.loopg/pramana-mcp declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.