refd agent-facing API
46
AI ReadinessFoundational (D)46/100
Official vendor OpenAPI document · agent-readyMarketingSeo Semoauth27 EndpointsREST
For Agents
Read a workspace's AI-answer visibility data from refd by listing and calling its read tools over one JSON-RPC 2.0 endpoint, after an OAuth 2.1 PKCE grant scoped to the selected workspaces.
Use for: I want to see how often my brand shows up in AI answers this month, Find which competitors appear instead of my brand for a tracked prompt, List all the read tools available on my refd workspace, Retrieve the citations behind a brand mention in an AI answer
Not supported: Does not handle classic search rankings, backlink analysis, or ad campaign management. Use for reading a workspace's brand visibility in AI-generated answers only.
The refd agent-facing API gives an agent read access to a workspace's AI visibility data: where a brand appears in AI-generated answers, which competitors appear instead, and the evidence behind each mention, citation, position, and score. It does this through a single stateless JSON-RPC 2.0 tool endpoint, where the agent lists the available read tools and a metric glossary at runtime and then calls them. The rest of the surface is the OAuth 2.1 machinery around it: protected-resource and authorization-server metadata, dynamic client registration, and an authorization-code flow with PKCE whose grant covers the workspaces chosen at consent.
Install Jentic One Beta
Connect the refd agent-facing API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the refd agent-facing API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Frefd.ai%2Frefd" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Frefd.ai%2Frefd" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with refd agent-facing API.
Discover the read tools a workspace grant exposes by sending a tools/list JSON-RPC request to POST /mcp
Call a refd read tool with a tools/call request to pull brand mentions, citations, and positions in AI answers
List the metric glossary with resources/list so the agent interprets refd scores correctly
Register an OAuth client dynamically through POST /oauth/register before starting the consent flow
Exchange an authorization code and code_verifier for an access token, or renew it with a refresh_token, at POST /oauth/token
Read the OAuth protected-resource and authorization-server metadata to configure a client automatically
Use Cases
Patterns agents use refd agent-facing API for, with concrete tasks.
★ AI visibility reporting agent through Jentic
A marketing agent that reports on AI search presence needs refd data without a developer hand-building the OAuth 2.1 PKCE flow. Through Jentic the agent searches for 'read my brand's AI answer visibility', loads POST /mcp with its JSON-RPC schema, sends tools/list to see the read tools the workspace grant allows, and then sends tools/call for the one it needs. The access token is injected at call time, and the agent turns the result into a summary of where the brand appeared and where a competitor took its place.
POST /mcp with {"jsonrpc":"2.0","id":1,"method":"tools/list"}, pick the tool that returns brand mentions, then POST /mcp with method tools/call for that tool and summarise the mentions and citations it returns
Interpreting visibility scores with the metric glossary
Visibility scores mean little without their definitions. refd exposes a metric glossary as a resource on the same JSON-RPC endpoint, so an agent can send resources/list and read how each score, position, and citation metric is defined before it writes a report. That keeps a weekly summary consistent with how refd itself computes the numbers.
POST /mcp with method resources/list, read the metric glossary entry for the visibility score, and include its definition in the report footer
Self-configuring OAuth client for refd
A developer connecting a new agent client to refd can let it configure itself. GET /.well-known/oauth-protected-resource/mcp names the authorization servers, GET /.well-known/oauth-authorization-server returns the endpoints, POST /oauth/register creates a client, and GET /oauth/authorize starts the PKCE flow that ends at a workspace consent screen. POST /oauth/token then exchanges the code and code_verifier for a token, and the refresh_token grant keeps it current.
GET /.well-known/oauth-authorization-server, POST /oauth/register to obtain a client_id, then POST /oauth/token with grant_type authorization_code, code, redirect_uri, client_id, and code_verifier
Key Endpoints
7 endpoints — the refd agent-facing api gives an agent read access to a workspace's ai visibility data: where a brand appears in ai-generated answers, which competitors appear instead, and the evidence behind each mention, citation, position, and score.
METHOD
PATH
DESCRIPTION
POST
/mcp
JSON-RPC 2.0 tool endpoint
POST
/oauth/token
Exchange a code or refresh token for an access token
GET
/oauth/authorize
Start the authorization-code plus PKCE flow
POST
/oauth/register
Register an OAuth client dynamically
GET
/.well-known/oauth-authorization-server
Read authorization-server metadata
GET
/health
Liveness probe
POST
/mcp
JSON-RPC 2.0 tool endpoint
POST
/oauth/token
Exchange a code or refresh token for an access token
GET
/oauth/authorize
Start the authorization-code plus PKCE flow
POST
/oauth/register
Register an OAuth client dynamically
GET
/.well-known/oauth-authorization-server
Read authorization-server metadata
GET
/health
Liveness probe
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
R
refd agent-facing API
- Foundational (D)46/100
83
Foundational Compliance58
Developer Experience & Jentic Compatibility20
AI-Readiness & Agent Experience94
Agent Usability90
Security84
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.2
Show dimension breakdown
83
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: ASignals: 4
99%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
100%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
35%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
58
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: C+Signals: 4
7%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
25%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
20
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
26%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
0%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
53%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
90
Security
Trust, risk posture, and security compliance.
Grade: A+Signals: 1
90%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
84
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: ASignals: 1
84%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring refd by hand means reading its OAuth discovery metadata, registering a client, running the authorization-code flow with PKCE, refreshing tokens, and then speaking JSON-RPC 2.0 to the tool endpoint. Through Jentic you install once, import refd from the API Directory, store the token once, and your agent calls it.
Permission scoping
refd sends every data request through one JSON-RPC endpoint and names the tool inside the request body, so rules bound which operations your agent may call, not which refd tool it invokes. Limit the agent to the tool endpoint it needs; token-minting operations like client registration or token exchange are not included unless you add them.
Credential isolation
Your refd access token is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'read my brand's AI answer visibility', and Jentic returns the matching refd operation with its JSON-RPC input schema so the agent sends a well-formed request without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using refd agent-facing API through Jentic.
What authentication does the refd agent-facing API use?
Per its OpenAPI spec, the refd API secures POST /mcp with OAuth 2.1 authorization code plus PKCE, declared as the mcpOAuth scheme with the data:read scope. The discovery, registration, authorize, token, and health endpoints need no credential, since they are how a client obtains the token in the first place. Through Jentic, the resulting token is held encrypted by your own Jentic One instance and injected at call time.
Is there a refd MCP server?
Yes - refd's agent interface is itself a remote MCP server over Streamable HTTP, and POST /mcp is that endpoint. You can also connect it through Jentic: your agent reaches the same endpoint without loading another server's tool definitions into its context, your OAuth token is injected at call time by your self-hosted instance instead of living in a client config file, and your rules decide which operations the agent may call.
What are the rate limits for the refd API?
The OpenAPI spec states that the tool endpoint is rate-limited per token but does not give a number. Check the refd agent documentation at https://refd.ai/agents for current limits before scheduling frequent report runs.
How do I pull brand visibility data from refd through Jentic?
Search Jentic for 'read my brand's AI answer visibility' to load POST /mcp, send a JSON-RPC request with method tools/list to see the read tools your grant allows, then send method tools/call with the chosen tool and its arguments. To run it on your own infrastructure, install Jentic One from its GitHub repo.
Which workspaces can an agent read with a refd grant?
A refd grant covers the workspaces selected on the consent screen during the OAuth authorize step, or all of them if you choose that. The spec describes access as read-only by default, so a data:read token can read visibility data for those workspaces without changing it.
Can I limit what my agent is allowed to do with the refd API?
Yes. Write a rule that allows only POST /mcp and leaves out the OAuth registration and token operations, so the agent can query visibility data with the token you stored but cannot register clients or mint new tokens. Workspace reach is set separately at OAuth consent, and every call the agent makes is logged.
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