io.github.Roberton003/mcp-server-decisions
PYPI · MCP-SERVER-DECISIONS
Decision tracking with prediction validation and outcome gates for AI agents
Available components
Last scanned (5 hours ago)
Scores higher than 80% of PyPI servers
Category Memory and Knowledge
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
- No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
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 (MIT).Pass
- Actively maintained (last published 105 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability73
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 434 tokens (~108/item across 4 items; 4 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management87
- Stability observed for 26 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 4 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 4 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities40
- Spec-recency check failed: implements MCP spec 2025-03-26; the latest is 2026-07-28. See how to fix → Fail
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 +1
No change was recorded against any check on this day. Stability & Change Management went from 83 to 87. That category is still filling its 30-day observation window: 25 days of observed history at the previous scan, 26 at this one. The score rises as the window fills, whether or not the server changes.
- 4 Nov 26 +12
- Malware scan: unverified → pass ▲ security
- Stability: pass → 0.83 functional
- 3 Nov 26 −15
- Malware scan: pass → unverified ▼ security
- 29 Oct 26 +1
- Stability: 0.97 → pass security
- 28 Oct 26 −1
- Stability: pass → 0.97 functional
- 22 Oct 26 +1
- Stability: 0.97 → pass security
- 21 Oct 26 −1
- Stability: pass → 0.97 functional
- 18 Oct 26 +15
- Malware scan: unverified → pass ▲ security
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/mcp-server-decisions@1.0.2
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 0 packages
| Packages resolved | 0 |
|---|---|
| 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 →
query-decisions ~77
Search prior decisions by keyword, technology, or domain
| Name | Type | Req | Description |
|---|---|---|---|
| domain | string | – | Partial domain filter |
| keyword | string | – | Search in problem + solution + alternatives (case-insensitive) |
| max_results | integer | – | Maximum results to return |
| technology | string | – | Exact technology filter (e.g., 'duckdb') |
No output schema declared.
No examples provided.
record-decision ~165
Register a technical decision with problem, solution, alternatives, and technologies
| Name | Type | Req | Description |
|---|---|---|---|
| adr_ref | string | – | Reference to an associated ADR, if any (e.g., 'docs/adr/adr-012-duckdb.md') |
| chosen_solution | string | yes | The solution that was chosen |
| domain | string | – | Technical domain (e.g., 'data-engineering', 'backend', 'ai') |
| predictions | array | – | Initial predictions known at decision time (optional) |
| problem | string | yes | The problem or technical opportunity identified |
| rejected_alternatives | array | yes | Alternatives considered and rejected |
| status | string | – | Decision status |
| technologies | array | yes | Technologies involved in this decision (e.g., ['duckdb', 'parquet']) |
No output schema declared.
No examples provided.
record-outcome ~110
Close the prediction loop: record actual results and calculate accuracy
| Name | Type | Req | Description |
|---|---|---|---|
| accuracy_score | integer | yes | Accuracy of prediction (0-100). >=90 excellent, 50-89 acceptable, <50 failed |
| actual_value | string | yes | Observed result (e.g., 'latency p99 = 180ms') |
| measurement_source | string | yes | Where the measurement came from |
| prediction_id | string | yes | Prediction ID (e.g., 'PRD-2026-0001') |
No output schema declared.
No examples provided.
record-prediction ~82
Register a measurable prediction linked to a decision
| Name | Type | Req | Description |
|---|---|---|---|
| decision_id | string | yes | Decision ID (e.g., 'DEC-2026-0001') |
| predicted_value | string | yes | Expected result (e.g., 'latency p99 < 200ms', 'cost < $100/month') |
| prediction_type | string | yes | Type of prediction |
No output schema declared.
No examples provided.
How do I install the io.github.Roberton003/mcp-server-decisions server?
io.github.Roberton003/mcp-server-decisions runs locally as a PyPI package, launched with uvx mcp-server-decisions. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · mcp-server-decisions
claude mcp add roberton003-mcp-server-decisions -- uvx mcp-server-decisions
What is the io.github.Roberton003/mcp-server-decisions server?
io.github.Roberton003/mcp-server-decisions is listed in the public MCP registry as io.github.Roberton003/mcp-server-decisions. Decision tracking with prediction validation and outcome gates for AI agents. This page covers its PyPI package (mcp-server-decisions).
Is the io.github.Roberton003/mcp-server-decisions server safe to use?
io.github.Roberton003/mcp-server-decisions scores 80 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.Roberton003/mcp-server-decisions server expose?
io.github.Roberton003/mcp-server-decisions exposes 4 tools: record-decision, record-prediction, record-outcome, query-decisions. Their descriptions and schemas cost roughly 434 tokens of context every time the server is loaded.
Is the io.github.Roberton003/mcp-server-decisions server still maintained?
io.github.Roberton003/mcp-server-decisions 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.Roberton003/mcp-server-decisions server under?
io.github.Roberton003/mcp-server-decisions declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.