Mcp Sequentialthinking Tools
Repository: mcp-sequentialthinking-tools
Author: spences10 · Source status: Clear source
🧠 An adaptation of the MCP Sequential Thinking Server to guide tool usage.
Score basis:Clear source · Low risk signals · Universal
Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Selected skills (2/4)
Comparison matrix
Highlights show current best; tooltip explains diff/best rules.
SAS-v2.1 diff rules / risk tag notes
Start with the matrix. Open this section when you need to understand audit grades, top threats, control gaps, and best-value highlights.
Suggested baseline
Repository: mcp-sequentialthinking-tools
Author: spences10 · Source status: Clear source
🧠 An adaptation of the MCP Sequential Thinking Server to guide tool usage.
Score basis:Clear source · Low risk signals · Universal
Search to add skills, or paste 2–4 comma-separated slugs.
How differences are detected
A row is marked different when selected skills have distinct values. Only-differences mode hides rows that are identical.
How best values are highlighted
Audit score, evidence confidence, trust score, and community signal prefer higher values; execution risk and install friction prefer lower values.
How to read risk tags
Risk tags come from SAS-v2.1 public-evidence signals and point to command, network, secret, context, or supply-chain items to review before install.
Selected audit signals
mcp-mindmesh
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, memory context poisoning
Control gaps:missing license, broad permissions, shell without guardrails
UnrealGenAISupport
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | mcp-mindmesh | UnrealGenAISupport |
|---|---|---|
| SAS-v2.1 pre-install audit | ||
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, human approval gap |
Evidence confidence | 67% | 65% |
| Source & provenance | ||
Provenance | 7ossamfarid/mcp-mindmesh | prajwalshettydev/UnrealGenAISupport |
Freshness | 2026-04-06 | 2026-03-26 |
| Community | ||
Stars | 5 | 515 |
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