Eppo MCP server: now part of Datadog Experiments
Why searching for an Eppo connector finds nothing, which 22 Datadog tools replace it, and what an agent can start, conclude or cancel with them.
Checked 3 October 2026 · from geteppo.com, its documentation sitemap and Datadog's tool reference
One of 91 guides to monitoring and developer tools. Each covers what an AI coding agent can get out of the tool through MCP, the protocol that lets the agent query the tool directly.
Summary
Eppo has not published an MCP server of its own as of 3 October 2026, and its documentation never mentions one. Its sitemap held 238 URLs on 3 October 2026, and not one of them contains the word MCP.
The reason is on Eppo's own homepage: Eppo is now Datadog Experiments, under a banner reading Eppo has been acquired by Datadog!
Datadog's hosted server carries the capability. Its 352-tool list, read on 6 October 2026, holds 14 experiment tools and 8 feature flag tools.
Those 22 tools go well past reading. An agent can create an experiment, start it, cancel it with a required reason, and conclude it with a permanent winning variant.
What is the Eppo MCP server?
Eppo was an experimentation platform: define a metric, split traffic with a feature flag, and get a statistically defensible answer about which variant won.
Datadog acquired it, and the product now ships as Datadog Experiments alongside Datadog Feature Flags. The concepts survive: experiments, variants, primary metrics, subject types (what each unit of traffic is, such as a user or a session) and allocations (how that traffic is split).
Reaching them from an agent means connecting Datadog's hosted MCP server. There is no separate Eppo endpoint, and there never was.
What a search for an Eppo connector actually finds:
| Route | What is there | State |
|---|---|---|
| Eppo documentation | 238 URLs, none mentioning MCP | Nothing to connect |
The Eppo-exp GitHub organization | No MCP repositories | Zero results on 25 August 2026 |
| Datadog's hosted server | Experiments and Feature Flags toolsets | 22 tools, inside a 352-tool server |
Eppo's site still resolves independently and still carries its own product pages. The acquisition banner is what explains the missing connector.
Experimentation sits in release, and the surrounding Datadog server reaches much further.
| Part of the work | What Eppo has here | Can an agent reach it |
|---|---|---|
| Code, tests & review | Flag implementation checks | Partial. check_datadog_flag_implementation asks whether a flag is implemented in code, and nothing reads a diff |
| CI & release | Experiments, variants, flags, environments and allocations | Yes. Full for experimentation. Creating, starting, cancelling and concluding an experiment are all tools |
| Production observability | Experiment results and diagnostics | Partial through these tools. The wider Datadog server covers metrics, logs and traces separately |
| Agent observability & evals | None in these toolsets | No. Datadog covers it elsewhere, not here |
| AI cost management | None | No spend data in either toolset |
For an agent, that means the whole experiment lifecycle is reachable, from creating one to declaring a winner. The statistical judgment stays in Datadog; what the agent gets is a verdict field and a health summary.
What can an AI agent do with Eppo?
22 tools in the two relevant toolsets: 14 for experiments and 8 for feature flags.
- Reading experiments9
list_experimentsget_experimentget_experiment_resultsget_experiment_diagnosticsexplore_experiment_resultslist_experiment_segmentation_propertiesget_experiment_segmentation_property_valuesget_metric_definitiondiagnose_experiment_run_failure- Changing experiments5Write
create_experimentstart_experimentcancel_experimentconclude_experimentlink_feature_flag_to_experiment- Reading feature flags5
list_datadog_feature_flagsget_datadog_feature_flaglist_datadog_feature_flag_environmentslist_datadog_feature_flag_allocationscheck_datadog_flag_implementation- Changing feature flags3Write
create_datadog_feature_flagupdate_datadog_feature_flag_environmentsync_datadog_feature_flag_allocations
Counted from Datadog's own tool reference, read on 6 October 2026, a 352-tool server in total. These 22 are the ones that carry what Eppo used to do; the other 330 cover the rest of Datadog.
What the tool definitions cost in context
A client that loads every tool definition at the start of a session spends this much context before the first question. Claude Code defers definitions by default through tool search, and loads a tool's definition when the agent needs it. The method below gives the version and date measured.
A context window is the amount of text a model can hold at once. Eppo has not published a server of its own, so the measurement covers Datadog's Experiments and Feature Flags toolsets. Twenty-two tools cost 1,786 to 2,082 tokens on Claude.
An agent reaching Eppo's experiment data pays this through Datadog's connector in most clients, unless the client defers tool loading.
| Tool set | Tools | Tokens (GPT-5.6, GPT-5.5) | Tokens (GPT-4, GPT-3.5) | Tokens (Claude Haiku 4.5 to Opus 5) | Share of a 200,000-token window |
|---|---|---|---|---|---|
| Every tool documented | 22 | 713 to 902 | 700 to 889 | 1,786 to 2,082 | 0.4% to 1.0% |
Encodings: GPT-5.6, GPT-5.5 o200k_base; GPT-4, GPT-3.5 cl100k_base; Claude Haiku 4.5 to Opus 5 count_tokens. Measured on or before 1 September 2026.
Counted from the 22 Experiments and Feature Flags entries in Datadog's tool reference. That reference is the only public inventory.
The hosted server needs real keys. So no live tools/list was captured, and no input schemas are available. These figures cover each tool's name and description only. They are a floor, not the figure.
The Claude columns are measured through the API's count_tokens endpoint with an empty schema per tool. So they cover the same content as the GPT columns. The range there is two tokenizer generations. Haiku 4.5 and Opus 4.6 are at the low end. Opus 5 and Sonnet 5 are at the high end. The gap between them is about a fifth.
Eppo MCP server limits: where answers come back incomplete
The first item below sends readers looking for a connector that does not exist. Read it before the caveats about live experiments.
There is no Eppo connector, and Eppo's own documentation never says so.
The Eppo documentation sitemap held 238 URLs on 25 August 2026 and none contains MCP, agent or assistant. The Eppo-exp GitHub organization returned zero MCP repositories.
The answer is on the marketing site rather than in the docs: a banner reading Eppo has been acquired by Datadog! and a headline reading Eppo is now Datadog Experiments.
Guard: Search Datadog's tool reference for experiment tools, not Eppo's documentation for a connector.
The agent says: “I concluded the experiment for you.” Datadog calls that a permanent decision.
conclude_experiment concludes a running experiment with a permanent winning variant decision. It sits beside read tools with similar names.
Guard: Gate the five experiment write tools behind approval, conclude_experiment above all.
The agent says: “Variant B won.” Nobody checked the sample ratio.
get_experiment_results returns a verdict field of better, worse or inconclusive. get_experiment_diagnostics is a separate call, and a sample ratio mismatch invalidates the verdict.
Guard: Require diagnostics alongside any verdict, as the disclosure block above does.
The agent says: “I synced the allocations.” In a named environment, possibly production.
sync_datadog_feature_flag_allocations and update_datadog_feature_flag_environment both take an environment, and nothing in the tool name distinguishes staging from production.
Guard: Have the agent name the environment before the call, not after it.
How to configure Eppo MCP for agents
- 1
Stop looking for an Eppo endpoint
There is none, and the documentation confirms it: 238 URLs with no MCP page.
- 2
Connect Datadog instead
The hosted server at
mcp.datadoghq.com/v1/mcpis the whole route. - 3
Narrow the toolsets
Twenty-two of the 352 are relevant here, and a client that loads every definition upfront spends context on the other 330.
- 4
Read the diagnostics before the results
get_experiment_diagnosticsreturns a sample ratio mismatch check. A sample ratio mismatch means the traffic each variant actually received does not match the split you configured, which is the standard reason a result should not be believed. - 5
Decide who may conclude an experiment
conclude_experimentrecords a permanent winning variant decision.
Paste this into your agent’s instructions
An experiment result is a statistical claim, and the tools return a verdict field that reads like a plain answer. The block keeps the health check attached to it.
When you answer using Datadog Experiments MCP tools, state: - The experiment name and the primary metric the verdict refers to. - Whether get_experiment_diagnostics was called, and what it said about sample ratio mismatch. Do not report a verdict without it. - Whether the call changed anything. create, start, cancel and conclude all change a live experiment. Never state that data does not exist. State which tool you called and what it returned. Write your answer in ASD-STE100 Simplified Technical English. Use short sentences with one idea in each.
Do you need the MCP server at all?
Not always, and never under the Eppo name. The Datadog UI remains the direct route for reading a result, and it shows the confidence intervals a prose answer flattens.
For experimentation without the rest of Datadog, Statsig publishes its own server and covers gates, experiments and autotunes directly.
For flags alone, Flagsmith and Harness FME are narrower connections than a 352-tool server.
Eppo's own API documentation is still published, and remains the route for anything scheduled against the platform.
With MCP, a result, its health check and the flag behind it arrive in one conversation, which is the sequence a careful reading of an experiment needs anyway.
Connect Datadog, filter to Experiments and Feature Flags, and gate the eight write tools.
Eppo MCP server setup
Nothing installs under the Eppo name. Eppo is a Datadog company, and its coverage arrives through Datadog's hosted MCP server rather than through a server of its own.
An Eppo login on its own does not authenticate against Datadog's server. You need a Datadog account with the Product Analytics Experiments permissions.
There is nothing to download. The server is hosted, and the endpoint answered HTTP 401 to an unauthenticated call, which is what a live gated endpoint should do.
Claude Code
The bare command carries no credentials because the hosted server authenticates over OAuth. On first connect the client opens a browser to authorize against your Datadog organization.
Nothing is installed and nothing is stored locally beyond the session the browser flow establishes.
claude mcp add --transport http datadog \ https://mcp.datadoghq.com/v1/mcp
Cursor
In ~/.cursor/mcp.json. The entry points at Datadog's endpoint, because that is where the Eppo tools live, and the headers carry Datadog keys.
{"mcpServers":{"datadog":{
"url":"https://mcp.datadoghq.com/v1/mcp",
"headers":{"DD_API_KEY":"<your-api-key>",
"DD_APPLICATION_KEY":"<your-app-key>"}}}}Clients without the OAuth flow
Clients that cannot complete a browser authorization send Datadog's API and application keys as headers instead.
Those keys are Datadog's own, and their scopes in Datadog decide what any Eppo-related question can reach.
{"mcpServers":{"datadog":{
"url":"https://mcp.datadoghq.com/v1/mcp",
"headers":{"DD_API_KEY":"<your-api-key>",
"DD_APPLICATION_KEY":"<your-app-key>"}}}}Every other client
Each block below is the configuration for one client, with the file path and the key that client expects.
Check the account before the config
The most common failure here is not configuration. It is reaching the endpoint with an Eppo login and no Datadog organization behind it.
The probe below carries no credentials deliberately: a 401 confirms the endpoint is live and gated, which separates an account problem from a network one.
curl -s -o /dev/null -w "%{http_code}" -X POST \
https://mcp.datadoghq.com/v1/mcp # 401Read-only access, permissions and security
Eight of the 22 tools write
They create experiments and flags, start and cancel runs, conclude a winner, and change allocations in a named environment.
conclude_experimentis permanentDatadog's own description calls it a permanent winning variant decision, which is not a state an agent should reach unattended.
Allocation changes move real traffic
update_datadog_feature_flag_environmentandsync_datadog_feature_flag_allocationsact on a specific environment, production included.Cancelling requires a reason, and the model writes it
cancel_experimenttakes a required reason, so the audit trail records whatever the agent typed.The credential is a Datadog credential
It carries whatever the Datadog account can reach, which is far more than experiments.
Troubleshooting
- You cannot find an Eppo MCP server
- There is none. Eppo's documentation sitemap held 238 URLs on 25 August 2026 with no MCP page, and the
Eppo-expGitHub organization has no MCP repositories. - An Eppo login does not authenticate the server
- The server is Datadog's. It authenticates with Datadog credentials, and the Eppo product now ships as Datadog Experiments.
- The experiment will not start
start_experimentrequires a linked flag with an active allocation, a subject type and a primary metric.link_feature_flag_to_experimentis the tool that supplies the first of those.- The results look wrong
- Call
get_experiment_diagnosticsfirst. It returns a health summary including sample ratio mismatch status, which is the usual explanation for a result that does not make sense. - The analysis pipeline failed
diagnose_experiment_run_failureexists for exactly this. It diagnoses why the latest or a specific analysis run failed and returns the root cause.- Too many unrelated tools appear
- The server held 352 tools on 3 October 2026. Only the Experiments and Feature Flags toolsets are relevant here, so filter to them.
Eppo MCP server: Reference
| Item | Value |
|---|---|
| Eppo's own server | None |
| Eppo documentation URLs | 238, none mentioning MCP |
| Eppo GitHub MCP repositories | 0 |
| Eppo's status | Acquired by Datadog. Its homepage reads Eppo is now Datadog Experiments |
| Covering server | https://mcp.datadoghq.com/v1/mcp |
| Size of that server | 352 tools |
| Experiment tools | 14 |
| Feature flag tools | 8 |
| Write tools among them | 8 |
| Permanent action | conclude_experiment records a winning variant |
| Inventory source | Datadog's tool reference, read 3 October 2026 |
What the vendor documents
Eppo has not published a connector of its own, so the record is Eppo's acquisition notice and Datadog's description of the tools that replaced it.
| What was checked | What it shows |
|---|---|
| Eppo documentation URLs | 238 |
| Of those mentioning MCP | 0 |
| Eppo MCP repositories on GitHub | 0 |
| Size of the Datadog server | 352 tools |
| Experiment tools | 14 |
| Feature flag tools | 8 |
| Of those, write tools | 8 |
“Eppo is now Datadog Experiments.”
“Concludes a running experiment with a permanent winning variant decision.”
“Returns a health summary for an experiment before interpreting results: sample ratio mismatch (SRM) status.”
Eppo's documentation sitemap was fetched on 25 August 2026 and its 238 URLs were searched for MCP, agent and assistant, with no match. The Eppo-exp GitHub organization was searched for MCP repositories on the same date and returned zero. Tool names and descriptions come from Datadog's own tool reference, read 18 August 2026.
Should you connect an agent to Eppo?
Yes. Best for reading a verdict together with its health check, with every write tool gated.
- Strongest fit
- Teams already on Datadog who ran experiments on Eppo and want an agent reading results and flags.
- Main advantage
- The full experiment lifecycle is reachable, and the diagnostics that decide whether a result is trustworthy are a tool rather than a footnote.
- Main weakness
- The connector is 22 tools inside Datadog's 352-tool server, which is built for something wider than Eppo.
- Operational risk
conclude_experimentwrites a permanent winning variant decision, and allocation tools move traffic in a named environment.
From Oodle
One platform for agent traces and infrastructure
Agent traces usually sit in a different product from the rest of your telemetry, so when a slow database makes an agent slow the symptom is in one tool and the cause is in another. Oodle keeps both in one query surface.
See agent observabilityFrequently asked questions
Does Eppo have an MCP server?
No. Its documentation sitemap held 238 URLs on 25 August 2026 with no MCP page, and its GitHub organization has no MCP repositories.
Why doesn't Eppo have an MCP server?
Eppo's own homepage answers it. A banner reads Eppo has been acquired by Datadog! and the headline reads Eppo is now Datadog Experiments.
What replaced the Eppo MCP server?
Datadog's hosted server at mcp.datadoghq.com/v1/mcp. Its 352-tool list, read on 6 October 2026, holds 14 experiment tools and 8 feature flag tools.
Can an agent change an experiment?
Yes. It can create one, start it, cancel it with a required reason, conclude it with a permanent winning variant, and link a feature flag to it.
How do I know a result is trustworthy?
Call get_experiment_diagnostics. It returns a health summary including sample ratio mismatch status, which is a separate call from get_experiment_results.
Is there a lighter alternative?
Statsig publishes its own server for gates and experiments, and Flagsmith covers flags alone. Both are far smaller connections than Datadog's 352-tool server.