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Showing 3 resources for "data-science"
Saved
Active

Safety notes filter active — add entries to compare trust side by side.

Trust snapshot

3 results in this view

Claimed
0%(0/3)

2 trust signals differ in this sample: Source provenance, Submitter

Signals differ on Source provenance, Submitter — add entries to compare before you install.

Rollout signal scan

2 rollout risk signals in current results

Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.

3 scanned

Install payload

Install payload is broadly covered in current results.

good

100% (3/3)

Adoption queue

Browse adoption queue · balanced

1/3 visible results are in hold tier and need mitigation before adoption.

ready 0caution 2hold 1

Jupyter MCP Server

1 blockers: Metadata review

caution

50/100

Request metadata review from maintainers or internal owners.

Collect package checksum or signed artifact information.

mcp/jupyter-mcp-server · trust review · confidence 67%

Neo4j MCP Server

1 blockers: Metadata review

caution

50/100

Request metadata review from maintainers or internal owners.

Collect package checksum or signed artifact information.

mcp/neo4j-mcp-server · trust review · confidence 67%

hold

38/100

Request metadata review from maintainers or internal owners.

Document privacy posture and data handling expectations.

Collect package checksum or signed artifact information.

rules/python-data-science · trust review · confidence 50%

Decision confidence

Decision confidence scan · balanced

1/3 results are low-confidence and need review before adoption.

high 0medium 2low 1

Jupyter MCP Server

Address Metadata review, Package integrity before broader rollout.

medium

54/100

Missing: Metadata reviewMissing: Package integrity

mcp/jupyter-mcp-server · trust review

Neo4j MCP Server

Address Metadata review, Package integrity before broader rollout.

medium

54/100

Missing: Metadata reviewMissing: Package integrity

mcp/neo4j-mcp-server · trust review

Freshness distribution

Mostly fresh with a few aging entries

Median age 52 days; 2 fresh, 1 aging or stale of 3 scanned.

median 52d

Aging

91–180 days

0%

0 entries

Stale

> 180 days

33%

1 entry

Theme distribution

Results center on data-science

67% of this view shares the top theme. Leading themes: data-science, python, code-execution.

Focused

13 distinct themes across 3 scanned

Jupyter MCP Server logo

MCP server for connecting Claude to Jupyter notebooks, kernels, files, cells, multimodal outputs, and JupyterLab workflows over stdio or Streamable HTTP.

Turn Claude into a practical pandas data-wrangling partner for loading, cleaning, reshaping, and aggregating tabular data with the pandas DataFrame API

Safety ✓ Privacy ·
Neo4j logo

Official Neo4j MCP server for giving Claude structured access to Neo4j graph schema introspection, read-only Cypher, optional write Cypher, and Graph Data Science procedure discovery.