Claude Code plugin

The LocalData MCP repository is also a Claude Code plugin. Its manifest, .claude-plugin/plugin.json, registers the localdata MCP server with the command uvx localdata-mcp and ships 18 skills and 11 agents that drive the tools documented in the tools reference.

Skills and agents call the MCP server; they add no analytical capability of their own. Everything they do is reachable by calling the tools directly.

Installing

Clone the repository and point Claude Code at it with --plugin-dir:

git clone https://github.com/ChrisGVE/localdata-mcp.git
claude --plugin-dir /path/to/localdata-mcp

Confirm what was picked up:

claude --plugin-dir /path/to/localdata-mcp plugin details localdata-mcp

That prints the component inventory — it should report 18 skills and 11 agents. claude --plugin-dir /path/to/localdata-mcp mcp list shows the MCP server as plugin:localdata-mcp:localdata; it launches through uvx, so the first start downloads the package and its dependencies.

claude plugin install localdata-mcp does not work yet. That command installs from a marketplace, and this repository does not ship a .claude-plugin/marketplace.json, so claude plugin marketplace add on it fails with “Marketplace file not found”. --plugin-dir is the supported route for now.

The MCP server on its own — without the skills and agents — needs no plugin machinery. Add it to any MCP client as described in getting started.

Using a skill

A skill is invoked by name as a slash command in a Claude Code session:

/forecast sales_db revenue

The arguments follow each skill’s argument-hint; forecast declares "<database-name> <column-name>". Claude also selects a skill on its own when the request matches its description, so “forecast next quarter’s revenue from sales_db” reaches the same place without the slash command.

Agents are not invoked by slash command. Claude delegates to one when a request matches the agent’s description, or you can ask for it directly — “use the forecaster agent on this series”.

Skills and agents call the MCP tools on your behalf, so the localdata server has to be connected first. Connect your data source with connect_database before invoking one; a skill has no way to guess which file or database you mean.

Skills

Each skill is a SKILL.md inside a group directory: skills/<group>/<skill-name>/SKILL.md. The manifest lists the five group directories under its skills key, and Claude Code scans one level below each of them — which is why the group directories are named individually rather than pointing at skills/ and relying on a recursive walk. Each skill declares an allowed-tools list restricting it to the tools it needs, and an argument-hint describing what to pass.

exploration/

Skill

Purpose

explore-data

Connect to a source, profile schema and quality, recommend which analyses fit

data-quality

Assess completeness, consistency, validity, and uniqueness before analysis

find-reference-data

Identify and prepare external reference data — benchmarks, demographics, economic indicators, geographic context

statistical/

Skill

Purpose

hypothesis-test

Check assumptions, select the test, report the result in plain language

ab-test

Analyze an experiment and return a ship / iterate / no-ship recommendation

analyze-correlations

Find strong relationships between variables and suggest regression models

sampling-estimation

Design a sampling strategy and estimate parameters with confidence intervals

modeling/

Skill

Purpose

regression

Fit and evaluate models predicting a target variable

cluster-analysis

Discover groupings, with cluster-count evaluation

anomaly-detection

Flag outliers with isolation forest or local outlier factor

dimensionality-reduction

Compress high-dimensional data with PCA, t-SNE, or UMAP

forecast

Analyze a time series and forecast forward with confidence intervals

geospatial

Distances, geographic clusters, accessibility

optimization

Resource allocation, scheduling, and process optimization under constraints

graph-data/

Skill

Purpose

graph-data-explore

Walk a DOT, GML, GraphML, or Mermaid graph — nodes, edges, statistics, paths, export

workflow/

Skill

Purpose

data-pipeline

End-to-end run: connect, profile, analyze, report

research-pipeline

Hypotheses, power analysis, assumption checks, reproducible reporting

process-control

Control charts, process stability and capability, out-of-control conditions

Agents

Agents live in agents/, one Markdown file per agent. All run on Sonnet; the turn budget in the table is the agent’s maxTurns and bounds how long an analysis may run before it must report back.

Agent

Turns

Scope

data-explorer

15

Profiles an unfamiliar dataset: schema, quality, patterns, summary report

data-scientist

30

Composes multi-step pipelines across domains when the right approach is unclear

statistical-analyst

20

Hypothesis tests, ANOVA, effect sizes, sampling design, bootstrap estimation, non-parametric tests

ml-analyst

25

Clustering, anomaly detection, dimensionality reduction, regression modeling

forecaster

20

Decomposition, stationarity testing, ARIMA/ETS choice, forecasts with uncertainty bounds

bi-analyst

20

A/B testing, cohort analysis, CLV, attribution, funnels; translates statistics into business recommendations

graph-data-analyst

15

Centrality, community detection, path finding, visualization export

geospatial-analyst

20

Coordinate systems, spatial relationships, distances, clustering, interpolation, accessibility

operations-analyst

20

Statistical process control, optimization, capacity planning, efficiency analysis

research-analyst

25

Methodological rigor: assumption documentation, power analysis, reproducible reporting

data-researcher

20

Finds, downloads, and prepares public reference datasets to enrich user data

Adding a skill or agent

Place a new skill in the domain directory it belongs to — skills/exploration/, skills/statistical/, skills/modeling/, skills/graph-data/, or skills/workflow/ — as <skill-name>/SKILL.md. The directory name is the skill name and must match the name field in the file’s frontmatter. Agents are a single agents/<agent-name>.md, with the same name-matching rule.

A new group directory has to be added to the skills array in .claude-plugin/plugin.json as well; a skill in a directory that is not listed there is not discovered, and nothing reports an error. Check with claude --plugin-dir . plugin details localdata-mcp — the skill count in the component inventory is the answer.