io.github.thyn-ai/algenta

up checked 2026-11-11T11:38:23.602Z

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Publisher-provided title

Algenta MCP Server

Publisher-provided description

Governed data discovery, exact queries, decisions, simulations, and runtime utilities over MCP.

Summary by lookupd

Lets agents onboard, query, and govern saved data connectors and repositories, plus run decision and simulation workflows.

Install

Claude Code, remote (streamable-http)

claude mcp add --transport http algenta https://api.algenta.ai/mcp

Claude Code, pypi package (stdio)

claude mcp add algenta -- uvx algenta-mcp

Codex, remote (streamable-http)

codex mcp add algenta --url https://api.algenta.ai/mcp

Codex, pypi package (stdio)

codex mcp add algenta -- uvx algenta-mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

{
  "mcpServers": {
    "algenta": {
      "url": "https://api.algenta.ai/mcp"
    }
  }
}

Cursor, pypi package (stdio) → .cursor/mcp.json

{
  "mcpServers": {
    "algenta": {
      "command": "uvx",
      "args": [
        "algenta-mcp"
      ]
    }
  }
}

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (showing 30 of 140)

Publisher-provided text

• onboard_dataset Register a dataset for semantic querying. Pass column names, inline records, or raw CSV. The engine profiles roles automatically and starts background training.
• list_datasets List registered datasets and their current model tier. Use search plus compact mode for low-token discovery, then poll status or use the primary data tools once
• get_dataset_status Get the live training status and model tier of one dataset: whether semantic training is still running or the dataset is ready, and which model serves queries —
• retrain_dataset Re-trigger background semantic training for one dataset and return immediately with status and a confirmation message — the build runs asynchronously, so poll g
• connect_data High-level data onboarding flow. Use this instead of advanced connector/source tools for normal users. Connect data once, pick the table/file/endpoint, and get
• list_data List visible datasets for the current user. Use search plus compact mode first for low-token dataset discovery, then get_data_schema on the chosen dataset_id. R
• get_data_summary Get the low-token dataset selection summary for a saved dataset_id. Use this after list_data(search=..., compact=true) before paying for the full schema payload
• get_data_schema Get a saved dataset plus its schema and relationship metadata by dataset_id. Read-only and non-destructive; reads only the active API key's organization and is
• refresh_data Re-pull a saved dataset from its original database, API, or object-store origin using the stored connection and selection, and return the same envelope as conne
• disconnect_data Delete a saved dataset and disconnect it from future use. When no other dataset in the workspace still uses the backing saved connection, that connection is del
• register_source Advanced tool. Register a data source and get full schema profiling + join detection. Profiles every column (type, cardinality, fill rate, distribution). Detect
• list_sources Advanced tool. List all registered data sources for this org with their schema summaries. Use this to discover available tables before calling query_data or reg
• get_source_schema Advanced tool. Get the full schema for a specific registered source: column types, cardinality, fill rates, formula relationships, and detected join keys to oth
• list_connectors List the data connectors saved under the caller's organization — databases, APIs, file-backed, and repository sources — with id, name, connector_type, status (u
• create_connector Save one connector configuration (host, credentials, options) for later data onboarding, health checks, and schema browsing. config is encrypted at rest and the
• get_connector Fetch one saved connector by connector_id: name, connector_type, status, visibility, timestamps, and the config fingerprint — never the stored credentials. Use
• update_connector Partially update one saved connector: only the supplied fields change. Passing a new config replaces the encrypted credentials and resets the connector to untes
• test_connector Run a real connectivity test against one saved connector's stored config and persist the outcome as its live or error status with last_tested_at. This opens an
• browse_connector Discover what one saved connector exposes — files, tables, endpoints, or items — with discovery labels and metadata for choosing what to onboard. The connector
• preview_test_connector Run a real connectivity test against an inline connector definition without saving anything — the dry run for create_connector. This opens an actual connection
• preview_browse_connector Browse one inline connector definition without saving it to discover files, tables, endpoints, or items. This opens a real connection to the source and is rate-
• delete_connector Delete one saved connector by id. Use update_connector to change config without losing the saved definition. Deleting is idempotent: repeating the call on an al
• get_repository_intelligence_capabilities List globally supported Repository Intelligence languages and ranked support progress. Read-only and non-destructive. Check language support here before create_
• create_repository_snapshot Create or reuse an immutable, content-hashed snapshot of a saved repository connector (a connector of a repository type — find its id with list_connectors). Re-
• get_repository_snapshot Fetch one persisted immutable repository snapshot by repository_id and snapshot_id, including its resolved_revision, content_hash, file_count, language_counts,
• triage_repository Condense one repository snapshot into a bounded workspace evidence bundle for the planner: ranked suspect files and symbols with scored, budget-capped snippets.
• create_repository_decision_plan Create one stored, immutable repository DecisionPlan revision from a triage workspace evidence bundle and return its decision_plan_id plus the validated patch d
• query_repository_graph Walk the dependency graph of one persisted repository snapshot from optional file_path/symbol_name seeds and return impacted files and symbols with change-risk
• simulate_repository Score the patch risk of a stored repository DecisionPlan with the deterministic simulation engine and return the gated DecisionEnvelope whose apply gate apply_r
• run_repository_pipeline Run the whole repository-intelligence chain — snapshot, triage, plan, simulate — in one call and return the canonical repository envelope with every stage's res

Details

• Version: 1.0.31
• Transports: streamable-http, stdio
• Uptime (7 days): 100%
• Median latency: 359 ms
• First indexed: 2026-11-01T09:58:01.369Z
• Last seen in registry: 2026-11-01T09:58:01.469Z
• Repository: https://github.com/thyn-ai/algenta-sdk
• Website: https://algenta.ai

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