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docs: add v3.0 tool and model integration pages and fix stale references #763

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cf91000
fix: correct retired model ids and stale API references for v3.0
Himanshu040604 Sep 1, 2026
3c90ade
docs: add pages for the v3.0 tool and model integrations
Himanshu040604 Sep 1, 2026
10298a8
Potential fix for pull request finding
Himanshu040604 Sep 1, 2026
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33 changes: 31 additions & 2 deletions docs.json
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Expand Up @@ -1465,7 +1465,8 @@
"models/providers/native/xai/usage/live-search-agent-stream",
"models/providers/native/xai/usage/reasoning-agent"
]
}
},
"models/providers/native/xai/supergrok-oauth"
]
},
{
Expand Down Expand Up @@ -2022,6 +2023,16 @@
}
]
},
{
"group": "Ramp Router",
"pages": [
"models/providers/gateways/ramp/overview",
{
"group": "Usage",
"pages": []
}
]
},
{
"group": "Tuning Engines",
"pages": [
Expand Down Expand Up @@ -2226,6 +2237,7 @@
"tools/toolkits/search/seltz",
"tools/toolkits/search/serpapi",
"tools/toolkits/search/serper",
"tools/toolkits/search/serply",
"tools/toolkits/search/sofya",
"tools/toolkits/search/tavily",
"tools/toolkits/search/valyu",
Expand All @@ -2237,6 +2249,7 @@
{
"group": "Social",
"pages": [
"tools/toolkits/social/atomic-mail",
"tools/toolkits/social/discord",
"tools/toolkits/social/email",
"tools/toolkits/social/gmail",
Expand Down Expand Up @@ -2287,6 +2300,7 @@
"group": "Local",
"pages": [
"tools/toolkits/local/calculator",
"tools/toolkits/local/code-mode",
"tools/toolkits/local/coding",
"tools/toolkits/local/docker",
"tools/toolkits/local/file",
Expand All @@ -2309,6 +2323,7 @@
"tools/toolkits/models/azure-openai",
"tools/toolkits/models/gemini",
"tools/toolkits/models/groq",
"tools/toolkits/models/minimax",
"tools/toolkits/models/morph",
"tools/toolkits/models/nebius",
"tools/toolkits/models/openai"
Expand Down Expand Up @@ -2346,6 +2361,7 @@
"tools/toolkits/others/e2b",
"tools/toolkits/others/evm",
"tools/toolkits/others/fal",
"tools/toolkits/others/finance",
"tools/toolkits/others/financial-datasets",
"tools/toolkits/others/giphy",
"tools/toolkits/others/github",
Expand All @@ -2357,6 +2373,7 @@
"tools/toolkits/others/google-slides",
"tools/toolkits/others/jira",
"tools/toolkits/others/knowledge",
"tools/toolkits/others/knowledge-management",
"tools/toolkits/others/linear",
"tools/toolkits/others/llms-txt",
"tools/toolkits/others/lumalabs",
Expand All @@ -2383,6 +2400,7 @@
"tools/toolkits/others/user-control-flow",
"tools/toolkits/others/user-feedback",
"tools/toolkits/others/visualization",
"tools/toolkits/others/wavespeed",
"tools/toolkits/others/web-browser",
"tools/toolkits/others/webtools",
"tools/toolkits/others/yfinance",
Expand Down Expand Up @@ -3400,7 +3418,8 @@
"models/providers/native/xai/usage/live-search-agent-stream",
"models/providers/native/xai/usage/reasoning-agent"
]
}
},
"models/providers/native/xai/supergrok-oauth"
]
},
{
Expand Down Expand Up @@ -3942,6 +3961,16 @@
}
]
},
{
"group": "Ramp Router",
"pages": [
"models/providers/gateways/ramp/overview",
{
"group": "Usage",
"pages": []
}
]
},
{
"group": "Tuning Engines",
"pages": [
Expand Down
2 changes: 1 addition & 1 deletion examples/tools/brandfetch-tools.mdx
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Expand Up @@ -44,7 +44,7 @@ from agno.tools.brandfetch import BrandfetchTools
# Brand Search API

agent = Agent(
tools=[BrandfetchTools(async_tools=True)],
tools=[BrandfetchTools()],
description="You are a Brand research agent. Given a company name or company domain, you will use the Brandfetch API to retrieve the company's brand information.",
)

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6 changes: 3 additions & 3 deletions examples/tools/mcp/overview.mdx
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Expand Up @@ -8,7 +8,7 @@ description: "Enable Agno agents to interact with external systems via MCP inter
| [MCP GitHub Agent](/examples/tools/mcp/github) | Create a GitHub agent that uses MCP to explore, analyze, and provide insights about GitHub repositories. |
| [Groq + MCP = Lightning Fast Agents](/examples/tools/mcp/groq-mcp) | Create a high-performance filesystem agent by combining Groq's fast LLM inference with the Model Context Protocol (MCP). |
| [Include Exclude Tools](/examples/tools/mcp/include-exclude-tools) | Filter which MCP server tools an agent can use with include_tools and exclude_tools. |
| [Multiple Servers](/examples/tools/mcp/multiple-servers) | Connect one agent to Airbnb and Brave Search MCP servers at once using MultiMCPTools. |
| [Multiple Servers](/examples/tools/mcp/multiple-servers) | Connect one agent to Airbnb and Brave Search MCP servers at once using one MCPTools instance per server. |

@Himanshu040604 Himanshu040604 Sep 1, 2026

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Deliberate, and declared in the PR body ('Not fixable here - the regen queue'): the linked example pages carry source: frontmatter, so hand edits are silently overwritten at the next regeneration - the fix path runs through the agno repo's cookbooks, then examples_sync. The hand-written index cannot keep describing MultiMCPTools, which is removed in v3.0 and raises ImportError; these rows describe the examples as they regenerate, and the mismatch closes on the next sync.

| [Sequential Thinking](/examples/tools/mcp/sequential-thinking) | Pair the Sequential Thinking MCP server with YFinanceTools so an agent reasons step by step before comparing two stocks. |
| [MCP Airbnb Agent](/examples/tools/mcp/airbnb) | Create an agent that uses MCP and Gemini 2.5 Pro to search for Airbnb listings. |
| [Agno MCP](/examples/tools/mcp/agno-mcp) | Query the Agno docs MCP server over streamable HTTP with MCPTools and a Claude agent. |
Expand All @@ -35,6 +35,6 @@ description: "Enable Agno agents to interact with external systems via MCP inter
| [Dynamic Headers](/examples/tools/mcp/dynamic-headers/overview) | Dynamically send information to the MCP server via HTTP headers. |
| [Local Server](/examples/tools/mcp/local-server/overview) | Run a local FastMCP weather server over stdio and connect an Agno agent to it with MCPTools. |
| [Mcp Toolbox Demo](/examples/tools/mcp/mcp-toolbox-demo/overview) | Run Agno agents and workflows against a PostgreSQL database through the MCP Toolbox for Databases server. |
| [Sse Transport](/examples/tools/mcp/sse-transport/overview) | Connect agents to an MCP server over SSE transport using MCPTools and MultiMCPTools. |
| [Streamable Http Transport](/examples/tools/mcp/streamable-http-transport/overview) | Connect an Agno agent to a Streamable HTTP MCP server using MCPTools and MultiMCPTools. |
| [Sse Transport](/examples/tools/mcp/sse-transport/overview) | Connect agents to an MCP server over SSE transport using MCPTools. |
| [Streamable Http Transport](/examples/tools/mcp/streamable-http-transport/overview) | Connect an Agno agent to a Streamable HTTP MCP server using MCPTools. |
| [MCP BGPT Agent - Evidence-grounded scientific paper search](/examples/tools/mcp/bgpt) | Query the hosted BGPT MCP server over Streamable HTTP to search papers and surface methods, sample sizes, limitations, and conflicts of interest. |
4 changes: 2 additions & 2 deletions examples/tools/mcp/sse-transport/overview.mdx
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@@ -1,8 +1,8 @@
---
title: "Overview"
description: "Connect agents to an MCP server over SSE transport using MCPTools and MultiMCPTools."
description: "Connect agents to an MCP server over SSE transport using MCPTools."
---
| Example | Description |
|---------|-------------|
| [Client](/examples/tools/mcp/sse-transport/client) | Connect an OpenAI agent to an SSE MCP server with MCPTools, and to SSE plus stdio servers together with MultiMCPTools. |
| [Client](/examples/tools/mcp/sse-transport/client) | Connect an OpenAI agent to an SSE MCP server with MCPTools, and to SSE plus stdio servers together with one MCPTools instance per server. |

@Himanshu040604 Himanshu040604 Sep 1, 2026

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Same situation as the overview rows: the linked client page is generated (source: frontmatter) and sits on the regen queue in the PR body. Editing it by hand is overwritten at the next regeneration; the description matches the post-regen state.

| [Server](/examples/tools/mcp/sse-transport/server) | Start an example MCP server that uses the SSE transport. |
4 changes: 2 additions & 2 deletions examples/tools/mcp/streamable-http-transport/overview.mdx
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@@ -1,8 +1,8 @@
---
title: "Overview"
description: "Connect an Agno agent to a Streamable HTTP MCP server using MCPTools and MultiMCPTools."
description: "Connect an Agno agent to a Streamable HTTP MCP server using MCPTools."
---
| Example | Description |
|---------|-------------|
| [Client](/examples/tools/mcp/streamable-http-transport/client) | Show how to connect to MCP servers that use either SSE or Streamable HTTP transport using our MCPTools and MultiMCPTools classes. |
| [Client](/examples/tools/mcp/streamable-http-transport/client) | Show how to connect to MCP servers that use either SSE or Streamable HTTP transport using our MCPTools class. |

@Himanshu040604 Himanshu040604 Sep 1, 2026

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Same as the SSE overview: the linked client page is generated (source: frontmatter) and on the regen queue in the PR body. The description matches the post-regen state.

| [Server](/examples/tools/mcp/streamable-http-transport/server) | Start an example MCP server that uses the Streamable HTTP transport. |
2 changes: 1 addition & 1 deletion faq/import-errors.mdx
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Expand Up @@ -20,7 +20,7 @@ pip install -U 'agno[os,psycopg,sql,pgvector]'
| `google-genai` not installed or not at the latest version | `Gemini`, `GeminiEmbedder` | `pip install 'agno[google]'` |
| `groq` not installed | `Groq` | `pip install 'agno[groq]'` |
| No module named `fastapi` / `PyJWT` is not installed | `AgentOS` | `pip install 'agno[os]'` |
| `mcp` not installed | `MCPTools`, `MultiMCPTools` | `pip install 'agno[mcp]'` |
| `mcp` not installed | `MCPTools` | `pip install 'agno[mcp]'` |
| `fastmcp` not installed | `AgentOS(mcp_server=True)` | `pip install 'agno[mcp]'` |
| `sqlalchemy` not installed | `SqliteDb` | `pip install 'agno[sqlite]'` |
| `sqlalchemy` not installed | `PostgresDb` | `pip install 'agno[sql,psycopg]'` |
Expand Down
10 changes: 7 additions & 3 deletions knowledge/vector-stores/redis/overview.mdx
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Expand Up @@ -16,7 +16,11 @@ You can use Redis as a vector database with Agno.
uv pip install -U redis redisvl pypdf openai agno
```

For connecting to a remote Redis instance, pass your Redis connection string to the `redis_url` parameter and the index name to the `index_name` parameter of the `RedisDB` constructor.
For connecting to a remote Redis instance, pass your Redis connection string to the `redis_url` parameter and the index name to the `index_name` parameter of the `RedisDb` constructor.

<Note>
The vector store class was renamed from `RedisDB` to `RedisDb` in Agno v3.0; the old spelling still works as a deprecated alias. Because the session storage adapter in `agno.db.redis` is also named `RedisDb`, the vector store is additionally exported as `RedisVectorDb` — use that spelling when both are imported in the same module.
</Note>

For a local docker setup, you can use the following command:

Expand All @@ -34,15 +38,15 @@ import os

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.redis import RedisDB
from agno.vectordb.redis import RedisDb
from agno.vectordb.search import SearchType

# Configure Redis connection (from environment variables if available, otherwise use local defaults)
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/0")
INDEX_NAME = os.getenv("REDIS_INDEX", "agno_cookbook_vectors")

# Initialize Redis Vector DB
vector_db = RedisDB(
vector_db = RedisDb(
index_name=INDEX_NAME,
redis_url=REDIS_URL,
search_type=SearchType.vector, # try SearchType.hybrid for hybrid search
Expand Down
4 changes: 2 additions & 2 deletions knowledge/vector-stores/redis/usage/async-redis-db.mdx
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Expand Up @@ -11,14 +11,14 @@ import os

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.redis import RedisDB, SearchType
from agno.vectordb.redis import RedisDb, SearchType

# Configure Redis connection
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/0")
INDEX_NAME = os.getenv("REDIS_INDEX", "agno_cookbook_vectors")

# Initialize Redis Vector DB
vector_db = RedisDB(
vector_db = RedisDb(
index_name=INDEX_NAME,
redis_url=REDIS_URL,
search_type=SearchType.vector, # try SearchType.hybrid for hybrid search
Expand Down
4 changes: 2 additions & 2 deletions knowledge/vector-stores/redis/usage/redis-db.mdx
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Expand Up @@ -11,14 +11,14 @@ import os
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.redis import RedisDB, SearchType
from agno.vectordb.redis import RedisDb, SearchType

# Configure Redis connection
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/0")
INDEX_NAME = os.getenv("REDIS_INDEX", "agno_cookbook_vectors")

# Initialize Redis Vector DB
vector_db = RedisDB(
vector_db = RedisDb(
index_name=INDEX_NAME,
redis_url=REDIS_URL,
search_type=SearchType.vector, # try SearchType.hybrid for hybrid search
Expand Down
2 changes: 2 additions & 0 deletions models/compatibility.mdx
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Expand Up @@ -75,6 +75,7 @@ Each checkmark records a media path implemented by the adapter and corroborated
| `OpenRouterResponses` | | | | | |
| `Perplexity` | | | | | |
| `Portkey` | | | | | |
| `RampRouter` | | | | | |
| `Requesty` | | | | | |
| `Sambanova` | | | | | |
| `Siliconflow` | | | | | |
Expand All @@ -84,6 +85,7 @@ Each checkmark records a media path implemented by the adapter and corroborated
| `VLLM` | | | | | |
| `Claude` (Vertex AI) | ✅ | | | | ✅ |
| `xAI` | ✅ | | | | |
| `xAIResponses` | | | | | |
| `MiMo` | | | | | |

## Developer Resources
Expand Down
6 changes: 3 additions & 3 deletions models/providers/gateways/cerebras-openai/overview.mdx
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Expand Up @@ -9,7 +9,7 @@ description: Use Cerebras with Agno through an OpenAI-compatible interface.
Cerebras also exposes an OpenAI-compatible interface, so you can use it with tools and libraries built for the OpenAI API.

<Warning>
Agno v2.7.2 defaults `CerebrasOpenAI.id` to the retired `llama-4-scout-17b-16e-instruct` model. Set `id="gpt-oss-120b"` or another current [Cerebras model](https://inference-docs.cerebras.ai/models/overview) explicitly.
Cerebras deprecated `llama-4-scout-17b-16e-instruct` on 2025-11-03 — see [Cerebras's deprecation notice](https://inference-docs.cerebras.ai/support/deprecation). Agno v3.0 defaults `CerebrasOpenAI.id` to `gpt-oss-120b`; earlier Agno versions default to the deprecated model, so set `id="gpt-oss-120b"` or another current [Cerebras model](https://inference-docs.cerebras.ai/models/overview) explicitly there.
</Warning>

### Basic Usage
Expand Down Expand Up @@ -42,12 +42,12 @@ The `CerebrasOpenAI` class accepts the following parameters:

| Parameter | Type | Description | Default |
| ---------- | ---- | ------------------------------------------------------------- | ------------------------- |
| `id` | str | Model identifier (for example, "gpt-oss-120b") | "llama-4-scout-17b-16e-instruct" |
| `id` | str | Model identifier (for example, "gpt-oss-120b") | "gpt-oss-120b" |
| `name` | str | Display name for the model | "CerebrasOpenAI" |
| `provider` | str | Provider name | "CerebrasOpenAI" |
| `api_key` | str | API key (falls back to CEREBRAS_API_KEY environment variable) | None |
| `base_url` | str | URL of the Cerebras OpenAI-compatible endpoint | "https://api.cerebras.ai/v1" |
| `parallel_tool_calls` | Optional[bool] | Whether to run tool calls in parallel (set to False automatically for llama-4-scout-17b-16e-instruct) | None |
| `parallel_tool_calls` | Optional[bool] | Whether to run tool calls in parallel (set to False automatically for `llama-4-scout-17b-16e-instruct`, a model Cerebras has since retired) | None |

`CerebrasOpenAI` also supports the parameters of [OpenAI](/reference/models/openai).

Expand Down
6 changes: 3 additions & 3 deletions models/providers/gateways/cerebras/overview.mdx
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Expand Up @@ -7,7 +7,7 @@ description: Use Cerebras high-speed inference with Agno agents.
[Cerebras Inference](https://inference-docs.cerebras.ai/introduction) provides high-speed, low-latency AI model inference powered by Cerebras Wafer-Scale Engines and CS-3 systems. Agno integrates directly with the Cerebras Python SDK.

<Warning>
Agno v2.7.2 defaults `Cerebras.id` to the retired `llama-4-scout-17b-16e-instruct` model. Set `id="gpt-oss-120b"` or another current [Cerebras model](https://inference-docs.cerebras.ai/models/overview) explicitly.
Cerebras deprecated `llama-4-scout-17b-16e-instruct` on 2025-11-03 — see [Cerebras's deprecation notice](https://inference-docs.cerebras.ai/support/deprecation). Agno v3.0 defaults `Cerebras.id` to `gpt-oss-120b`; earlier Agno versions default to the deprecated model, so set `id="gpt-oss-120b"` or another current [Cerebras model](https://inference-docs.cerebras.ai/models/overview) explicitly there.
</Warning>

## Prerequisites
Expand Down Expand Up @@ -57,10 +57,10 @@ Cerebras currently serves the following models (see the [model list](https://inf

| Parameter | Type | Default | Description |
| ---------------------------- | ------------------------------ | ------------------------------------ | ------------------------------------------------------------------------------------------ |
| `id` | `str` | `"llama-4-scout-17b-16e-instruct"` | The ID of the Cerebras model to use |
| `id` | `str` | `"gpt-oss-120b"` | The ID of the Cerebras model to use |
| `name` | `str` | `"Cerebras"` | The name of the model |
| `provider` | `str` | `"Cerebras"` | The provider of the model |
| `parallel_tool_calls` | `Optional[bool]` | `None` | Whether to run tool calls in parallel (automatically set to False for llama-4-scout) |
| `parallel_tool_calls` | `Optional[bool]` | `None` | Whether to run tool calls in parallel (automatically set to False for `llama-4-scout-17b-16e-instruct`, a model Cerebras has since retired) |
| `max_completion_tokens` | `Optional[int]` | `None` | Maximum number of completion tokens to generate |
| `repetition_penalty` | `Optional[float]` | `None` | Penalty for repeating tokens (higher values reduce repetition) |
| `temperature` | `Optional[float]` | `None` | Controls randomness in the model's output (0.0 to 2.0) |
Expand Down
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