Honeyhive MCP server

Connect Honeyhive to Claude, ChatGPT, Cursor, Claude Code, Codex, Gemini, GitHub Copilot and any other MCP client, for your whole team. Metorial adds security, governance, and tracing, and gives everyone one Magic MCP URL to connect.

What you can do with the Honeyhive MCP server

Ask your agent in plain language. Each of these maps to a real tool on the server.

  • Use the delete prompt configuration tool in Honeyhive
  • Use the list experiment runs tool in Honeyhive
  • Use the delete dataset tool in Honeyhive
  • Use the post feedback tool in Honeyhive
  • Use the update event tool in Honeyhive
  • Use the get experiment run tool in Honeyhive

Supported Tools

delete_configuration

Delete Prompt Configuration

Delete a prompt configuration by its ID.

list_runs

List Experiment Runs

List evaluation/experiment runs in a project. Supports filtering by dataset, name, status, and pagination. Use this to find and compare past experiment results.

delete_dataset

Delete Dataset

Delete a dataset by its ID.

post_feedback

Post Feedback

Post user feedback or quality metrics against a specific event or session. Feedback data is used for monitoring, building evaluation datasets, and improving AI outputs over time.

update_event

Update Event

Update an existing event's metadata, feedback, metrics, outputs, or other fields. Use this to enrich trace data after the fact, such as attaching user feedback or quality metrics.

get_run

Get Experiment Run

Retrieve full details and results of an experiment run by its ID. Includes event IDs, dataset association, configuration, and metric results.

start_session

Start Session

Start a new tracing session in HoneyHive. A session represents a complete interaction or request and serves as the root of a trace tree. Child events (model, tool, chain) can be attached to it.

compare_runs

Compare Experiment Runs

Compare two experiment runs side by side. Shows metric differences, common datapoints, and per-event comparison details. Useful for detecting regressions or improvements between runs.

query_events

Query Events

Search and filter trace events using structured filters. Supports filtering by event type, metadata fields, date ranges, and more. Use for monitoring, debugging, and data exploration.

delete_run

Delete Experiment Run

Delete an experiment run by its ID.

update_dataset

Update Dataset

Update a dataset name, description, or datapoint membership.

delete_project

Delete Project

DEPRECATED — unavailable with project-scoped data-plane API keys. Manage projects in HoneyHive administration using separate control-plane credentials. This tool reports the limitation without making an API request.

create_metric

Create Metric

Create a new evaluation metric for a project. Metrics can be code-based (custom), LLM-as-a-judge (model), or human annotation (human). They define quality criteria for scoring AI outputs.

delete_metric

Delete Metric

Delete an evaluation metric by its ID.

list_datasets

List Datasets

List datasets in a project, optionally filtering by dataset ID. Dataset type filtering is unavailable on the current API. Datasets contain curated input/output pairs used for evaluations and experiments.

list_metrics

List Metrics

List all evaluation metrics defined for a project. Metrics are used to score and evaluate AI application outputs during experiments and production monitoring.

create_configuration

Create Prompt Configuration

Create a new prompt configuration (managed prompt) in a project. Configurations centralize prompt management with versioning and environment-based deployment.

log_event

Log Event

Log a single trace event (model, tool, or chain) in HoneyHive. Events are nested within sessions to build a distributed trace. Use this to record individual LLM calls, tool invocations, or chain steps.

log_event_batch

Log Event Batch

Log multiple trace events in a single batch request. Efficient for high-volume ingestion. All events can optionally share a single session.

get_session

Get Session

Retrieve a session by ID, including its trace fields and child event IDs.

list_projects

List Projects

DEPRECATED — unavailable with project-scoped data-plane API keys. Manage projects in HoneyHive administration using separate control-plane credentials. This tool reports the limitation without making an API request.

get_event

Get Event

Retrieve a single event by its ID, including its trace fields and child event IDs. The connection API key selects the project.

create_dataset

Create Dataset

Create a new dataset in a project. Datasets hold curated datapoints for running evaluations and experiments.

add_datapoints_to_dataset

Add Datapoints to Dataset

Add raw data records to a dataset with a field mapping. The mapping defines which fields from the raw data should be used as inputs, ground truths, and history.

update_configuration

Update Prompt Configuration

Update an existing prompt configuration's parameters, environments, or other settings.

update_metric

Update Metric

Update an existing metric's definition, criteria, or settings.

delete_event

Delete Event

DEPRECATED — unavailable: HoneyHive does not document an API for deleting individual events. Retained for existing workflows; invoking this tool reports the provider limitation.

get_run_result

Get Run Results

Retrieve detailed evaluation results for an experiment run, including pass/fail outcomes, metric aggregations, and per-datapoint details.

create_project

Create Project

DEPRECATED — unavailable with project-scoped data-plane API keys. Manage projects in HoneyHive administration using separate control-plane credentials. This tool reports the limitation without making an API request.

create_run

Create Experiment Run

Create a new evaluation/experiment run. Runs associate traced events with a dataset and configuration for evaluation and comparison.

list_configurations

List Prompt Configurations

List prompt configurations (managed prompts) in a project. Configurations can be filtered by environment and name. Use this to discover available prompts and their deployment status.

update_project

Update Project

DEPRECATED — unavailable with project-scoped data-plane API keys. Manage projects in HoneyHive administration using separate control-plane credentials. This tool reports the limitation without making an API request.

delete_session

Delete Session

DEPRECATED — unavailable: HoneyHive does not document an API for deleting individual sessions. Retained for existing workflows; invoking this tool reports the provider limitation.

update_run

Update Experiment Run

Update an experiment run name, status, configuration, metadata, or associated events and datapoints.

update_datapoint

Update Datapoint

Update evaluation datapoint inputs, expected outputs, history, metadata, or dataset associations.

list_datapoints

List Datapoints

List evaluation datapoints in a project, optionally filtering by dataset name or datapoint IDs. The connection API key selects the project.

delete_datapoint

Delete Datapoint

Delete an evaluation datapoint by its ID.

get_datapoint

Get Datapoint

Retrieve an evaluation datapoint by its ID. Call list_datapoints to discover IDs.

create_datapoint

Create Datapoint

Create an evaluation datapoint with inputs, expected outputs, conversation history, and optional dataset associations. The connection API key selects the project.

Connect Honeyhive to your AI client

Every client uses the same Magic MCP URL, and so does any other MCP client. Add it once and sign in with SSO.

  1. Enable Honeyhive in Metorial. In your Metorial portal, enable the Honeyhive MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
  2. Add a custom connector. Open Customize, then Connectors. Select Add, then Custom, then Web.
  3. Paste your Metorial MCP URL. Name it Metorial, paste your Magic MCP URL (<your-magic-mcp-url>) and continue.
  4. Sign in. Select Add and sign in to load Honeyhive tools.

Run Honeyhive through the Metorial gateway

One governed layer for every app your agents reach, not a separate connector per tool.

  • Give Honeyhive and every other app to your whole team through one MCP gateway, behind your SSO.
  • Scope which teams and agents can use Honeyhive tools with role-based access control, and trace every call.
  • Prefer to run it yourself? Metorial is open source and self-hostable.

More integrations teams use with Honeyhive

Google Sheets

Create, read, and update spreadsheets and their cell data. Read and write values to individual cells, ranges, or multiple ranges using A1 notation or named ranges. Apply cell formatting including text styles, backgrounds, borders, number formats, and conditional formatting. Manage sheets (tabs) within a spreadsheet—add, delete, copy, rename, and reorder them. Create and manage embedded charts, pivot tables, filter views, data validation rules, protected ranges, named ranges, and merged cells. Perform batch operations to apply multiple updates atomically.

GitHub

Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.

Salesforce

Manage CRM data including Accounts, Contacts, Leads, Opportunities, Cases, and custom objects. Create, read, update, and delete records. Query data using SOQL and search across objects using SOSL. Perform bulk data operations for large-scale imports, exports, and migrations. Execute composite requests to batch multiple operations in a single API call. Access analytics, reports, and dashboards. Manage files and attachments associated with records. Interact with Chatter feeds, posts, and groups for social collaboration. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.

Sharepoint

Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Resolve site users to numeric Person/Group LookupId values. Upload, download, move, copy, and version files in document libraries. Search across sites, files, folders, lists, and list items using Microsoft Search. Manage permissions at site, list, and item levels with granular access control. Define and manage content types and site columns. Retrieve site properties and search for sites across Microsoft 365.

Airtable

Create, read, update, and delete records in Airtable bases and tables. Manage base schemas including creating tables and fields. Filter records using formulas, sort by fields, and scope queries to specific views. Upsert records to find, create, or update in a single call. Upload attachments to records, read and write record comments, list accessible bases, and receive real-time base change events through webhooks.

Google Drive

Upload, download, create, copy, move, rename, trash, and permanently delete files and folders in Google Drive. Search for files using complex queries filtering by name, MIME type, owner, modification date, labels, and other metadata. Share files and folders with specific users, groups, or domains with role-based permissions (owner, writer, commenter, reader). Manage shared drives and their members. Export Google Workspace files (Docs, Sheets, Slides) to standard formats like PDF, DOCX, and XLSX. Track file revision history and restore earlier versions. Create, read, update, and delete threaded comments and replies on files. Read label definitions and search files by label. Browse the Drive apps installed for your account. Store app-specific data in a hidden per-user folder.

Technical notes for Honeyhive

Trace, monitor, and evaluate LLM applications and AI agents. Create and manage projects, log distributed traces of AI application execution including model calls, tool invocations, and chain events. Run offline experiments against curated datasets with custom evaluators. Create, version, and manage datasets and prompts. Post user feedback and custom metrics against sessions or events. Query and analyze production traces with aggregated cost, latency, token usage, and quality metrics. Manage annotation queues for human feedback collection. Configure prompt deployments across environments.

Frequently asked questions

Common questions about connecting Honeyhive to AI agents with Metorial.

  1. How many tools does the Honeyhive MCP server have?
    The Honeyhive MCP server exposes 39 tools, including Delete Prompt Configuration, List Experiment Runs, Delete Dataset. Each one is governed and traced through Metorial.
  2. Honeyhive exposes tools your agents call on demand; it does not publish event triggers yet. Everything still runs through one governed MCP URL.
  3. Any MCP client, including VS Code, Windsurf, Zed, OpenCode and Grok. Each one reaches the Honeyhive MCP server through the same Metorial URL.
  4. Use role-based access control to decide which teams, users, and agents can use Honeyhive and which of its tools they can call.
  5. Yes. Metorial is open source, so you can run the Honeyhive MCP server yourself or use the hosted gateway.

Connect Honeyhive to production AI agents

See how Metorial gives your team governed access to Honeyhive, with tracing and security controls built in.