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Nexatron

PYPI · NEXATRON-MCP · 2 COMPONENTS

Ask business questions across your enterprise data in plain English, with Nexatron.

64 Trust /100

Last scanned (8 hours ago)

Scores higher than 61% of PyPI servers

Category Data and Analytics

Trust breakdown (7 categories)

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 31 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency19
Schema Quality & AI Usability82
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (good).Pass
  • Tool/resource definitions use about 635 tokens (~48/item across 13 items; 12 tools + 1 resources), lean.Pass
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
  • Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
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 12 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 14 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

Unverified: 1 category

A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

Changelog

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 +15
    • Malware scan: unverified → pass ▲ security
  • 4 Nov 26 49

    First indexed and scored.

Diagnostics

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/nexatron-mcp@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 31 packages
Packages resolved 31
No linked repository 1
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 12 exposed · ~567 tokens

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 →

Tool Tokens
detect_schema_drift ~51

Detect schema changes (drift) for a connection. Compares the current database schema to the last discovered schema and reports added/removed columns and type changes.

NameTypeReqDescription
connection_idstringyes–
NameTypeReqDescription
resultstringyes–

No examples provided.

get_credit_balance ~26

Check your remaining query credits. Shows current balance, period dates, and usage status.

Input schema present but exposes no named parameters.

NameTypeReqDescription
resultstringyes–

No examples provided.

get_report ~35

Get a saved report by ID. Returns the report title, description, type, and definition.

NameTypeReqDescription
report_idstringyes–
NameTypeReqDescription
resultstringyes–

No examples provided.

get_schema ~44

Get the database schema for a connection. Shows all tables and their columns with data types. Use list_connections first to get the connection_id.

NameTypeReqDescription
connection_idstringyes–
NameTypeReqDescription
resultstringyes–

No examples provided.

list_connections ~38

List all data source connections. Shows connection name, type (PostgreSQL, Snowflake, BigQuery, etc.), and current health status.

Input schema present but exposes no named parameters.

NameTypeReqDescription
resultstringyes–

No examples provided.

list_conversations ~30

List recent query conversations. Shows your recent natural language queries and timestamps.

NameTypeReqDescription
limitinteger––
NameTypeReqDescription
resultstringyes–

No examples provided.

list_metrics ~37

List all metrics in the semantic layer. Shows metric name, SQL expression, type, and certification status. Certified metrics have verified, governed definitions.

Input schema present but exposes no named parameters.

NameTypeReqDescription
resultstringyes–

No examples provided.

list_views ~33

List logical views in the semantic layer. Logical views are virtual tables that combine physical tables with business context and computed columns.

Input schema present but exposes no named parameters.

NameTypeReqDescription
resultstringyes–

No examples provided.

query ~95

Ask a question about your data in plain English. Nexatron translates your question into SQL, executes it against your data sources, and returns the answer with results. Examples: - "Show me total revenue by region for Q4" - "Which customers churned in the last 30 days?" - "Compare this month's sales to last month" - "Top 10 products by units sold"

NameTypeReqDescription
questionstringyes–
NameTypeReqDescription
resultstringyes–

No examples provided.

search_knowledge_base ~115

Search across knowledge bases using natural language. Finds relevant document chunks from uploaded PDFs, docs, and notes. Useful for finding business context, definitions, or policies. top_k is 1-100. A chunk longer than max_chars (default 500) is shown up to that length and labelled as an excerpt with both lengths, its chunk_id and its document_id. max_chars=null returns full chunks.

NameTypeReqDescription
max_chars–––
querystringyes–
top_kinteger––
NameTypeReqDescription
resultstringyes–

No examples provided.

test_connection ~36

Test connectivity to a data source. Verifies that Nexatron can reach the database and returns latency.

NameTypeReqDescription
connection_idstringyes–
NameTypeReqDescription
resultstringyes–

No examples provided.

whoami ~27

Show your Nexatron user info and tenant. Returns your email, roles, and organization name.

Input schema present but exposes no named parameters.

NameTypeReqDescription
resultstringyes–

No examples provided.

Install

How do I install the Nexatron MCP server?

Nexatron runs locally as a PyPI package, launched with uvx nexatron-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 · nexatron-mcp

# add to Claude Code
claude mcp add io-nexatron-mcp -- uvx nexatron-mcp
Common questions

What is the Nexatron MCP server?

Nexatron is an MCP server listed in the public MCP registry as io.nexatron/mcp. Ask business questions across your enterprise data in plain English, with Nexatron. This page covers its PyPI package (nexatron-mcp).

Is the Nexatron MCP server safe to use?

Nexatron scores 64 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 Nexatron MCP server expose?

Nexatron exposes 12 tools: query, list_connections, get_schema, test_connection, detect_schema_drift, and 7 more. Their descriptions and schemas cost roughly 567 tokens of context every time the server is loaded.

Is the Nexatron MCP server still maintained?

Nexatron 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 Nexatron MCP server under?

Nexatron declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.