Fibery MCP connector for AI agents

Tools your project management agent reaches for on Fibery, scoped per user.

CALL ANY TOOL

92 tools for Fibery: query, search, and fetch workspace data, create and update entities, edit documents and comments, and manage spaces, databases, fields, views, and reports.

fiberymcp_add_chart_tab

Add chart tab

Appends a new chart tab to an existing Fibery report. **Prerequisite:** You need a `reportId` from `create_report` or `get_reports_list`. Call `display_report_schema` first to discover valid field expressions for the report's sources. Reports are a specialized domain, call `get_fibery_skill` with `skill: "reports"` for the full report model, expression syntax, palettes, conditions, and workflow.

Parameters

Name

Type

Required

Description

reportId

string

Required

UUID of the report to add the chart tab to (from create_report or get_reports_list).

array

Required

X-axis dimensions. Put categorical/date dimensions before numeric.

array

Required

Y-axis dimensions. Put categorical/date dimensions before numeric.

color

object

Optional

Color-coding (legend) dimension. Only one allowed.

description

string

Optional

Tab description.

dimensionConditions

array

Optional

Dimension-level filters (must reference expressions already used in the tab).

fieldConditions

array

Optional

Field-level filters applied to this tab's data.

label

array

Optional

Label dimensions shown on chart points/bars.

palette

string

Optional

Color palette. See get_fibery_skill(skill:'reports') for palette selection guidance. One of: `fibery2.0`, `category10`, `accent`, `dark2`, `paired`, `pastel1`, `pastel2`, `set1`, `set2`, `set3`, `setL`, `tableau10`, `brown_blue_green`, `purple_red_green`, `pink_yellow_green`, `purple_orange`, `red_blue`, `red_grey`, `red_yellow_blue`, `red_yellow_green`, `spectral`, `blues`, `greens`, `greys`, `oranges`, `purples`, `blue_green`.

size

object

Optional

Size-coding dimension. Only one allowed.

title

string

Optional

Tab title.

type

string

Optional

Chart type. Defaults to 'scatterplot' if omitted. See get_fibery_skill(skill:'reports') for chart-type guidance. One of: `line`, `scatterplot`, `stacked-bar`, `bar`, `stacked-area`, `area`.

fiberymcp_add_comment

Add comment

fiberymcp_add_metric_tab

Add metric tab

fiberymcp_create_automation

Create automation

fiberymcp_create_custom_app_dev_token

Create custom app dev token

fiberymcp_create_icon_fields

Create icon fields

fiberymcp_create_report

Create report

fiberymcp_delete_automation

Delete automation

fiberymcp_delete_comments_fields

Delete comments fields

fiberymcp_delete_entities

Delete entities

fiberymcp_delete_space

Delete space

fiberymcp_display_automations_schema

Display automations schema

fiberymcp_display_schema_capabilities

Display schema capabilities

fiberymcp_execute_code

Execute code

fiberymcp_fetch_by_url

Fetch by url

fiberymcp_get_automation

Get automation

fiberymcp_get_connectors_list

List get connectors

fiberymcp_get_entity_mention

Get entity mention

fiberymcp_get_manual_import_link

Get manual import link

fiberymcp_move_document_blocks

Move document blocks

fiberymcp_query

Query

fiberymcp_read_document

Read document

fiberymcp_remove_collection_items

Remove collection items

fiberymcp_replace_block_text

Replace block text

fiberymcp_resolve_document_suggestions

Resolve document suggestions

fiberymcp_search

fiberymcp_set_block_attrs

Set block attrs

fiberymcp_update_automation

Update automation

fiberymcp_update_formula_field

Update formula field

fiberymcp_update_single_select_fields

Update single select fields

For more tools, view docs.

Build your Agent

Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.

import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Fibery MCP tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fiberymcp"], toolNames: [
    "fiberymcp_schema",
    "fiberymcp_query",
    "fiberymcp_update_entities"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Which high-priority bugs are still open in the Product space?" }] });

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fiberymcp"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Which high-priority bugs are still open in the Product space?" }],
  tools,
});

// Execute the tool call with the user's vaulted Fibery token
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fiberymcp"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Which high-priority bugs are still open in the Product space?" }],
  tools,
});

// Tool call runs with the user's vaulted Fibery token
await sk.tools.executeTool(msg.content, "user_123");

import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fiberymcp"] }, pageSize: 100,
});

const agent = new Agent({
  name: "project_agent",
  model: "gemini-2.5-pro",
  instruction: "Fibery MCP tools scoped to this user",
  tools,
});

await agent.run("Which high-priority bugs are still open in the Product space?");

Try these prompts

Copy any prompt into your agent. Each maps directly to a Fibery MCP tool. Click to copy, paste into your agent, done.

Query and search

Copy the prompt

Copied

Which high-priority bugs are still open in the Product space?

Copy the prompt

Copied

Search the workspace for everything about the onboarding redesign.

Copy the prompt

Copied

Show recent activity history in the Roadmap space.

Create and update

Copy the prompt

Copied

Create a feature request titled Bulk export in the Product database.

Copy the prompt

Copied

Move this task to Done and add a comment summarizing the fix.

Copy the prompt

Copied

Assign all unassigned bugs in this sprint to Priya.

Docs, views, and reports

Copy the prompt

Copied

Add a Risks section to the Q4 planning document.

Copy the prompt

Copied

Create a board view of open tasks grouped by state.

Copy the prompt

Copied

Create a report that charts open bugs by priority.

SEE HOW AUTH WORKS

Each user signs in to Fibery once; Scalekit stores and refreshes their tokens. Credentials stay vaulted, every call is scope checked, and every action is logged.

Authorize

Your user connects

Fibery MCP

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Fibery MCP

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Fibery MCP

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Fibery MCP

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other project management connectors.

Engineering Teams

Engineering standup agent

Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.

Support and Ops Teams

Meeting prep

Pulls agenda, participant context, and open action items before every meeting.

Engineering Teams

Auto release notes agent

Reads merged GitHub PRs, groups them into structured release notes, publishes the page to Notion, and announces the release in Slack. Every call runs on the engineer's own delegated OAuth.

Support and Ops Teams

Support triage agent

Fetches new Zendesk tickets, classifies them by type and urgency, searches the Notion knowledge base for an answer, and routes what it cannot resolve to Slack. Every call runs on the support agent's own delegated OAuth.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared Fibery token looks fine in a demo. In production every entity update and comment looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.

// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Fibery today. Ten connectors tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Fibery as the user or through a shared service account?

As the user. Each user signs in to Fibery once, and Scalekit stores and refreshes their tokens. Audit logs attribute every action to that user, not a shared service account.

Where is the Fibery OAuth token stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.

Can I limit what the agent does in Fibery?

Yes. Filter by tool name in listScopedTools to expose only what you want, for example the read tools plus fiberymcp_update_entities, without schema or delete tools. Scalekit also enforces scope checks before every API call.

What happens when a user revokes Fibery access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Can the agent change my Fibery workspace structure?

Yes, if you expose those tools. Beyond entities and documents, Fibery MCP can create and delete spaces, databases, fields, and views. 30 of the 92 tools are destructive. Many deletions are restorable via the Activity Log, but fiberymcp_delete_entities is permanent. Leave schema and delete tools out of toolNames to keep the agent on querying and updating entities.