Eodly MCP server
Allows team members to check in via Discord, and the server provides access to the resulting end-of-day reports.
Provides end-of-day reports that weigh claims against real work activity in GitHub.
Provides end-of-day reports that weigh claims against real work activity in Linear.
Allows team members to check in via Slack, and the server provides access to the resulting end-of-day reports.
Allows team members to check in via Telegram, and the server provides access to the resulting end-of-day reports.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Eodly MCP serverwho is slipping this week?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Eodly MCP server
Read your team's sourced end-of-day reports and roster from any MCP client. Sign in with your Eodly account, or use an Eodly API key.
Sign in (OAuth): https://eodly.io/mcp (Streamable HTTP, nothing to install, works on every Eodly plan including the free one; a founder or lead approves the connection). With an API key: https://eodly.io/api/mcp (send Authorization: Bearer eodly_sk_...), or locally with npx @eodly/mcp (stdio) and EODLY_API_KEY set to a key created in the app under Settings, Developer, API keys. Tools: whoami, list_reports, get_report, list_team. MCP Apps: report tools render as an interactive card in hosts that support the UI extension. Read-only, and scoped to one organization.
Eodly sends founders and team leads one sourced report every evening: who shipped, who is silent, who is slipping. Your team checks in from Slack, Telegram or Discord, and Eodly weighs each claim against the real work in GitHub and Linear. This server exposes those reports to MCP clients such as Claude and Cursor, so you can ask an agent "who is slipping this week?" and have it pull the sourced answer.
Read-only. It cannot change anything in your workspace.
Install
Sign in with Eodly (recommended)
Add a custom connector with this URL. The client opens an Eodly page where you sign in and choose Allow; no key to create or paste:
https://eodly.io/mcpWorks in Claude, Gemini CLI and any client that supports MCP OAuth. Remove access any time in Eodly under Settings, Developer, Connected apps.
Hosted, with an API key
The same server for clients that take a header instead of a sign-in. Send the key as Authorization: Bearer eodly_sk_...:
https://eodly.io/api/mcpLocal (stdio)
npx @eodly/mcpRelated MCP server: linear-mcp
Configure
For the local server or the API-key endpoint, create an API key in the Eodly app under Settings → Developer → API keys, then add the server to your client.
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"eodly": {
"command": "npx",
"args": ["-y", "@eodly/mcp"],
"env": { "EODLY_API_KEY": "eodly_sk_..." }
}
}
}Cursor and other MCP clients use the same shape.
Tools
Tool | What it does | Scope |
| Identify the connected workspace and the scopes the connection holds | none |
| Recent end-of-day report summaries, most recent first ( |
|
| Full structured content of one report by id |
|
| The team roster: names, roles, departments |
|
Interactive report card (MCP Apps)
list_reports and get_report ship an interactive view alongside their JSON. In a host that supports the MCP Apps UI extension (SEP-1865), the report renders as a card (who shipped, who's silent, who's slipping) instead of a wall of text. Hosts without the extension get the same JSON as before, so nothing breaks.
Resource |
|
MIME type |
|
Capability |
|
The view is fully self-contained (inline CSS and JS, no network access, no external assets) and declares an empty CSP allowlist. The hosted endpoints (https://eodly.io/mcp and https://eodly.io/api/mcp) serve the identical view.
Environment
Variable | Required | Default |
| yes | none. An Eodly API key ( |
| no |
|
Keys are organization-scoped and read-only. Revoke one at any time in the app.
Links
License
MIT. See LICENSE.
Available Tools
4 toolsget_reportAInspect
Get the full structured content of a single end-of-day report by id (use list_reports to find ids). Requires the reports:read scope.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The report id (UUID). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does disclose the required auth scope (reports:read), which an agent needs before invoking. It also characterizes the return as 'full structured content,' implying a complete read with no pagination or filtering. It does not cover rate limits or error behavior, keeping it below a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with zero filler, front-loading the operation and the resource before the parenthetical pointer to the id source. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read tool with no output schema, the description covers what is fetched, how it is keyed, where to get the key, and the auth requirement. The only mild gap is that 'full structured content' does not hint at the shape of the returned report, but nothing essential to correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single id parameter is fully documented in the schema (UUID, minLength 1), so the baseline is 3. The description adds the practical pointer that ids come from list_reports, which helps the agent obtain a valid value, but adds no format or constraint detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (Get) and resource (a single end-of-day report) with the retrieval key (by id), and explicitly differentiates from the sibling list_reports, which handles collections rather than single records. An agent can distinguish this from list_reports without opening either schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Names the alternative (list_reports) and the condition that selects it (to find ids), which is genuinely useful routing guidance. It stops short of stating when not to use this tool or any prerequisite beyond scope, so it is clear context rather than a full when/when-not map.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_reportsAInspect
List recent end-of-day report summaries for the organization, most recent first. Requires the reports:read scope.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max reports to return (1-50, default 14). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description must carry the behavioral burden. It does disclose two useful traits — the required reports:read auth scope and that results come back most recent first as summaries rather than full reports — but says nothing about read-only safety, failure modes, or the default window it draws from.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with zero filler; the resource/scope statement is front-loaded and the auth requirement trails it as a prerequisite.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter list tool with no output schema, the definition covers resource, scope, ordering, and auth. It omits only secondary details such as what fields a summary contains and pagination behavior, which are minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single limit parameter (1-50, default 14), so the schema fully documents it. The description adds no format, ordering, or interaction detail beyond what the schema already supplies, which is the baseline case.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb+resource: lists end-of-day report summaries scoped to the organization, ordered most-recent-first. It describes the scope precisely but never names how it differs from the sibling get_report, which an agent must infer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"List recent" and the reports:read scope prerequisite imply when the tool is usable, but there is no explicit when-to-use versus get_report, and no statement about what happens when no reports exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_teamBInspect
List the team roster for the organization (names, roles, departments). Requires the team:read scope.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does add one genuinely useful behavioral detail beyond the schema — the required team:read scope — and 'list' implies a read-only, no-side-effect operation, but it says nothing about pagination, result size, or whether the roster is org-wide vs a caller's team.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core action and with no filler. Slightly better if the scope requirement were merged or placed consistently, but there is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless read tool with no output schema, the description covers what the tool returns (names, roles, departments) and the auth requirement, which is nearly everything an agent needs. Only return-shape details like counts or pagination are absent, which is acceptable here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing to disambiguate and the schema cannot add meaning. Baseline 4 applies; the parenthetical field list is descriptive of output rather than input, which is a minor bonus.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('List') and resource ('team roster for the organization') and names the returned fields (names, roles, departments), which distinguishes it from the report-oriented siblings. It does not explicitly contrast with whoami, but the roster scope is clear enough that an agent can pick it out.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use or when-not-to-use guidance is given, and no alternative is named, even though whoami overlaps conceptually with looking up people. The 'Requires the team:read scope' line is a prerequisite, not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
whoamiAInspect
Identify the API key: returns the Eodly organization it belongs to and the scopes it holds.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden. It does disclose the return content (organization + scopes), which is meaningful since no output schema exists, but it says nothing about behavior on an invalid/expired key, error cases, or that it is a side-effect-free read.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with the action front-loaded and the return payload trailing. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a trivial zero-parameter identification tool with no output schema, the description covers the essential behavior and the return values. Only error/edge-case behavior is unaddressed, which is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to clarify beyond the schema; baseline 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ("Identify") and resource ("the API key") and goes further to name what is returned: the Eodly organization and its scopes. That is unambiguous and easily separable from the sibling tools (list_reports, get_report, list_team), though it does not explicitly call out the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: an agent can infer this is the tool for checking which org/scopes a key belongs to, but the description gives no explicit when-to-use trigger, no prerequisites, and no mention of alternatives. Adequate but leaves routing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
v0.2.1- First observed
get_report - First observed
list_reports - First observed
list_team - First observed
whoami
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: whoami identifies the API key, list_reports and get_report separate listing from retrieval, and list_team targets the team roster. There is no meaningful overlap that would cause misselection.
list_reports, get_report, and list_team follow a consistent verb_noun pattern. whoami is a common identity command but breaks the pattern, making it a minor deviation rather than a major inconsistency.
Four tools is a reasonable, well-scoped set for a read-only reporting and team-access server. It is slightly lean, but each tool earns its place and there are no redundant entries.
The surface covers identity, report listing and retrieval, and team roster access, which is coherent for a read-only integration. Minor gaps exist, such as no team member detail lookup or report filtering, but core read workflows are covered.
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