Algenta MCP Server

Connect Remote server

claude mcp add --transport http algenta https://api.algenta.ai/mcp --header "Authorization: Bearer <YOUR_API_KEY>"

{
  "mcpServers": {
    "algenta": {
      "url": "https://api.algenta.ai/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_API_KEY>"
      }
    }
  }
}

{
  "servers": {
    "algenta": {
      "type": "http",
      "url": "https://api.algenta.ai/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_API_KEY>"
      }
    }
  }
}

Settings > Connectors > Add custom connector
URL: https://api.algenta.ai/mcp

Replace the values in angle brackets with your own. Keys stay on your machine; we never see them.

Tools 80 found in our last check

• 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. Queries work immediately via a fallback model — accuracy improves once schema-specific training completes (poll status…

• 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 you choose a dataset. Read-only and non-destructive; lists only the active API key's organization and is not separatel…

• 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 — model_tier 'none' = deterministic fallback only, 'base' = generic model, 'schema' = fully trained schema-specific mode…

• 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 get_dataset_status until model_tier reaches 'schema'. Use after schema changes, alias updates, or to force a fresh model…

• 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 a reusable dataset_id. If the result status is needs_selection, call connect_data again with connection_id and the chos…

• 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. Read-only and non-destructive; lists only the active API key's organization and is not separately rate-limited. Returns…

• 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. Read-only and non-destructive; reads only the active API key's organization and is not separately rate-limited. Retur…

• 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 not separately rate-limited. Use get_data_summary first for a low-token look. Returns the dataset record and its schema…

• 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 connect_data (status, schema_summary, refreshable). Only datasets created from a live connection can refresh — an inline upl…

• 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 deleted too and connection_deleted is true in the response. Requires manage permission on the dataset (access_scope_denied…

• register_source

  Advanced tool. Register a data source and get full schema profiling + join detection. Profiles every column (type, cardinality, fill rate, distribution). Detects formula relationships (A×B≈C) within the source. Detects join keys to every already-registered source automatically.…

• 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 register_source. Read-only and non-destructive; not separately rate-limited. Returns the sources array with each source's…

• 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 other sources. Read-only and non-destructive; not separately rate-limited. Use list_sources to find source ids. Returns so…

• 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 (untested, live, error), and visibility; stored credentials are never returned. Paginated with page and limit; status fil…

• 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 new connector starts untested — call test_connector to verify it reaches the source, then browse_connector to discover…

• get_connector

  Fetch one saved connector by connector_id: name, connector_type, status, visibility, timestamps, and the config fingerprint — never the stored credentials. Use list_connectors to find ids. Read-only; an unknown or invisible id fails with not_found.

• 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 untested, so call test_connector again afterwards. Requires manage permission on the connector (access_scope_denied otherwis…

• 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 actual connection to the source. Use preview_test_connector for an unsaved inline definition, and browse_connector once…

• 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 must be live: an untested or errored connector fails with not_connected, so run test_connector first. Use preview_brows…

• 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 to the source, is rate-limited per organization, and caches successful outcomes briefly. Nothing is persisted. Returns…

• 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-limited per organization; nothing is saved. Use browse_connector for saved connectors. Returns connector_type, items, t…

• 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 already-deleted or never-existing id returns success with already_absent: true instead of an error. Returns connector_id…

• 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_repository_snapshot. Returns supported_languages and support_progress (ranked target counts, progress fraction, and lab…

• 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-running with identical inputs returns the existing snapshot (status='existing') instead of duplicating it. The snapshot…

• 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, and graph artifact refs. Use this to re-read a snapshot created earlier with create_repository_snapshot (or through run…

• 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. signals seeds the search — pass issue_text, diagnostics, failing_tests, changed_files, and/or workspace_context. The r…

• 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 diff inline. snapshot_id is resolved from the bundle when omitted. This is the only LLM-touching stage of the repository…

• 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 scores. Seed scope comes from snapshot_id or a triage workspace_evidence_bundle_ref — one of the two is required. direc…

• 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_repository checks. snapshot_id is resolved from the plan when omitted. runs pins the scenario count (100 or more; omit f…

• 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 response, stage timings, and the ids (snapshot_id, plan_id, simulation_id) the apply step needs. Pass snapshot_id to reuse…

• simulate_repository_patch

  Simulate the risk of an in-flight unified diff against one persisted snapshot and return the canonical repository envelope — without creating a stored decision plan. Use this to verify a working-tree patch mid-run; use simulate_repository when a stored DecisionPlan already exist…

• run_repository_fix

  Run the repository pipeline and then apply its result in one call, returning the canonical repository envelope for both stages. pipeline takes run_repository_pipeline's arguments and must complete through simulate (the call fails otherwise); apply takes apply_repository's argume…

• apply_repository

  Materialize a simulated repository decision in one of three modes. patch_only just returns the validated patch diff with applied=false and writes nothing. local_branch commits the patch to a new branch (default algenta/<plan-suffix>) in the engine-side checkout and returns commi…

• query_data

  Execute a structured query against connected data sources. Convert the user's question to a structured intent and call this tool — do NOT try to write SQL or parse column names yourself. The engine resolves column meaning from mathematical relationships and statistical structure…

• query_batch

  Execute several governed exact queries in one API call. Use this for multi-metric prompts after choosing a dataset with list_data and get_data_summary. Each item reuses the same structured query contract as query_data; defaults may provide shared dataset_id, filter, limit, and o…

• query_sql_report

  Execute a constrained read-only SQL rowset query over authorized datasets. Use this only for wide reports that do not fit the governed exact-query surface. SQL must be a single SELECT/WITH statement over the provided dataset aliases. Returns columns, rows, row_count, truncated,…

• ingest_data

  Auto-map tabular data to a simulation payload. Detects variable distributions, polarity (revenue=positive, cost=negative), units, and builds the objective function automatically. Set run_simulation=true to execute the simulation immediately and get results. Multiple tables: auto…

• list_models

  List the current Algenta model catalog, including deterministic utility models and any provider-backed routed entries with their routing, failover, timeout, and auth metadata, including capability-specific chat and embedding auth/header readiness. Use this before calling tokeniz…

• resolve_artifact_bridge

  Resolve a Hugging Face artifact path through the Algenta compatibility-ring artifact bridge. Defaults to cache-only lookup and never downloads unless local_files_only=false. Use this only for Hugging Face artifact paths; use list_models for the model catalog. Returns the resolut…

• tokenize

  Tokenize UTF-8 text into individual tokens with a supported deterministic Algenta tokenizer model (default text.tokenizer; call list_models for every supported model id). Use this when you need the token strings themselves; call count_tokens when you only need the number. Read-o…

• count_tokens

  Count how many tokens a supported deterministic Algenta tokenizer model produces for UTF-8 text (default text.tokenizer; call list_models for every supported model id). Use this for prompt-size checks and token budgeting; call tokenize when you also need the token strings. Read-…

• chat_completions

  Run one ordered chat transcript through an Algenta model and return the assistant message plus token usage. The default text.tokenizer model is a deterministic tokenizer-backed utility route whose assistant message is a JSON tokenization summary of the user messages — not a gene…

• responses

  Run the unified Algenta utility response surface: deterministic tokenization/embeddings, or (for provider-backed chat models) a chat response with optional function/tool calling. `input` accepts a plain string, a list of independent strings (each processed as its own single-turn…

• embeddings

  Generate one embedding vector per input string (a single string or a list of strings). The default text.hash_embedding_v1 model produces deterministic lexical hash embeddings — identical input always yields the identical vector; provider-backed embedding models advertised by lis…

• embedding_similarity

  Score the similarity between two caller-supplied embedding vectors with a supported deterministic metric (default embeddings.cosine_similarity). This tool does not generate embeddings from text — call embeddings first to produce the vectors. left and right must have equal length…

• rerank

  Rank caller-supplied document embeddings against a query embedding with a supported deterministic similarity metric (default embeddings.cosine_similarity), most relevant first. This tool does not embed text — call embeddings first to produce the query and document vectors. Every…

• list_runtime_libraries

  List executable local-runtime Mojo libraries. Use this when you need the runtime-backed compute catalog rather than the governed data/query tools. This surface is local/runtime-backed only.

• execute_runtime_library

  Execute one local-runtime Mojo library function by module and function name. Pass args as either a JSON object, array, scalar, or null. This surface is local/runtime-backed only and does not route through hosted data/query APIs.

• list_capability_providers

  List the unified capability providers available to the organization — data sources, MCP servers, skill packs, native tools, and runtime libraries — with their profiles, auth kinds, supported execution owners, and binding scopes. Start here to find provider_id and profile_id for…

• list_capability_bindings

  List the capability bindings saved under the caller's organization, optionally narrowed by provider_id or scope (user, workspace, organization). A binding pairs a provider profile with credentials/config and is what makes capabilities executable. Use create_capability_binding to…

• create_capability_binding

  Save one capability binding for a provider/profile pair and return it with its binding_id. scope (default workspace) decides who can use it, execution_owner decides where executions run (algenta_managed on the engine, client_managed in the customer app or adapter path), and conf…

• test_capability_binding

  Run a health test on one capability binding and return the outcome. Pass binding_id to test a saved binding, or a full inline definition (provider_id, profile_id, config, ...) to preview-test one that was never saved — nothing is persisted in the preview form. Use this after cre…

• discover_capability_binding

  Discover the capabilities one binding exposes and return them as catalog entries. Pass binding_id to discover a saved binding (this publishes or refreshes its capabilities in the catalog), or a full inline definition to preview-discover one that was never saved. Call this after…

• list_capabilities

  List the unified capability catalog visible to the caller — datasets, MCP tools, resources and prompts, skills, native tools, and runtime libraries — with each entry's kind, provider, binding, and execution owner. Filter by kinds, provider_ids, or binding_ids to narrow the catal…

• get_capability

  Fetch one unified capability catalog entry by capability_id: kind, provider, binding, execution owner, approval requirement, and tags. include_instruction=true also returns the skill instruction text. Find capability ids with list_capabilities or route_capabilities. Read-only; a…

• route_capabilities

  Pick the best unified capability for a natural-language objective and return the route plan: the selected capability, binding, and kind, the authoritative execution_owner, whether approval is required, confidence and reason, plus ordered fallbacks (max_fallbacks, default 3). The…

• execute_capability

  Execute one routed or known algenta_managed capability by capability id and return the execution receipt. client_managed routes must execute in the customer app or adapter path — this tool will not run them. If the capability requires approval (approval_required), this returns a…

• list_skills

  List the skill capabilities in the unified capability plane — prompt skills enabled for the caller's organization with their names, bindings, and execution owners. This is list_capabilities narrowed to kind=skill. Use enable_skill to add one and disable_skill to remove one. Read…

• enable_skill

  Enable one prompt skill as a first-class capability binding and return its discovered catalog entry. The skill's instruction text becomes an instruction_only capability under the caller's user scope, selectable by route_capabilities. Persists a new binding; remove it with disabl…

• disable_skill

  Disable one skill by deleting its capability binding (find binding ids with list_skills or list_capability_bindings). The skill immediately stops appearing in the capability catalog and can no longer be routed or executed; the deletion is permanent. Disabling is idempotent: repe…

• plan_decision

  Run a validated simulation-style request (the same payload contract as simulate) but return only the structured DecisionPlan summary — the compact plan object with recommended action and calibrated confidence, without the full DecisionEnvelope metrics. Use this when the caller n…

• product_decision

  Recommend an action for a business decision from plain inputs, and return the risk summary behind it. Each input becomes a simulation variable: fixed at value, or triangular when low and high bounds are given; inputs named cost/costs/expense/expenses/spending are subtracted in t…

• product_agent_run

  Execute a natural-language task synchronously with the simple product agent and return a compact task result. The agent picks one tool from the task wording (optimize for best/maximum-style tasks, simulate for risk/forecast-style, search for find/lookup-style, otherwise calculat…

• product_optimize

  Estimate the best value for each decision variable given a plain-English objective, and return the per-variable optima. Every variable is sampled uniformly over its [min, max] range; an objective containing 'maximize' favors each variable's max, anything else favors the min, and…

• product_retrieve

  Rank caller-supplied documents against a search query and return the top matches with snippets. Scoring is deterministic lexical word-overlap between query and document plus a bonus when the query prefix appears in the document; results sort by relevance_score with rank starting…

• product_forecast

  Forecast a business metric horizon periods ahead from its historical series and return per-period point forecasts with confidence intervals. The trend comes from the last up-to-6 history values, volatility from the mean absolute period change, and a 5000-scenario simulation quan…

• simulate

  Run a Monte Carlo simulation and get a structured decision recommendation. Use for: quantifying risk in a decision, comparing expected outcomes, getting probability-weighted recommendations. Synchronous deterministic compute governed by the plan's per-minute rate limit and month…

• recommend

  Compare multiple named actions/options and get a ranked recommendation. Use when you need to choose between two or more alternatives with uncertainty. Synchronous deterministic compute; nothing is persisted and no separate rate limit applies. Returns recommended_action, confiden…

• score

  Run one simulation request (the same payload shape as simulate) and return the decision envelope fields plus a composite score with its breakdown. The score blends the normalized expected value and one minus the probability of loss; scoring_weights tunes the blend (expected_valu…

• batch

  Run multiple simulation requests in one call and return per-item success or failure details. Synchronous deterministic compute; nothing is persisted and no separate rate limit applies. Use simulate for a single request and submit_job for very large async runs. Returns total, suc…

• compare

  Run 2-10 named scenarios side by side and return the winner plus each scenario's deltas versus the best one. The winner is the scenario with the highest expected value; every entry reports its recommended_action, expected_value, probability_of_loss, and delta_vs_best. Each scena…

• submit_job

  Submit a long-running async simulation job. Use for n_simulations > 500,000 or when you need a callback. Returns a job_id — poll with get_job_status. Submitting persists the job under the active API key's organization; when callback_url is set, completion is delivered to it by o…

• list_jobs

  List the organization's async simulation jobs, newest first, with pagination (defaults page 1, limit 25, max 200) and an optional status filter such as queued, running, completed, failed, or cancelled. Each entry carries the job id, status, progress, and poll URL. Use get_job_st…

• get_job_status

  Fetch the latest async simulation job status by id. Read-only and non-destructive; not separately rate-limited. Use poll_job to block until a terminal state. Returns the job record with status, progress, timestamps, and poll_url.

• poll_job

  Wait for an async simulation job to reach a terminal state. Returns the final result when the job completes, or the terminal status when it fails, is cancelled, or times out. Read-only: it polls the job's status endpoints and changes nothing. Use get_job_status for a single non-…

• get_job_result

  Fetch the completed result payload for an async simulation job by id. Read-only and non-destructive; not separately rate-limited. Use get_job_status to check progress before the job completes. Returns the completed job's result payload.

• cancel_job

  Cancel a queued or running async simulation job by id. Use this for queued or running jobs; list_jobs shows their states. Cancelling is idempotent: repeating the call on an already-cancelled or never-existing id returns success with already_absent: true instead of an error; a co…

• test_webhook_delivery

  Send one real test webhook payload (event webhook.test with a sample message) to a callback URL and return the delivery result. This makes an actual outbound HTTP POST from the Algenta API to the given URL, with no retries. Use it to verify a receiver before wiring callback_url…

• create_agent_run

  Create a persisted agent run lifecycle resource for a natural-language task. With approval_mode=auto (default) the run picks a tool from the task wording, executes synchronously, and returns completed; approval_mode=manual parks it at requires_approval until approve_agent_run, a…

• list_agent_runs

  List the organization's persisted agent runs, paginated (defaults page 1, limit 25), with lineage-aware filters: status, request_hash (find reruns of the same request), policy_snapshot_id, and schema_snapshot_id (find runs under one policy or schema revision). Use get_agent_run…

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