Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
Scale parallelism. Preserve alignment. A fleet of coding agents builds one task in parallel against
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
CONCORD_ENGINE_DIRYou need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"concord-engine": {
"command": "npx",
"args": [
"-y",
"concord-engine"
],
"env": {
"CONCORD_ENGINE_DIR": "your-value"
}
}
}
}Run this in your terminal
claude mcp add concord-engine --env CONCORD_ENGINE_DIR=your-value -- npx -y concord-engineFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"concord-engine": {
"command": "npx",
"args": [
"-y",
"concord-engine"
],
"env": {
"CONCORD_ENGINE_DIR": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"concord-engine": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"concord-engine"
],
"env": {
"CONCORD_ENGINE_DIR": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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CONCORD_ENGINE_DIR envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account harsh-chandak, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.3.2) reached the registry 15 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Agent-Native Google Calendar - manage events, sync, and public booking
Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Scale parallelism. Preserve alignment.
Describe a task. A fleet of agents builds it. They come back with work that is finished, tested and documented — and that agrees with itself, because none of them was allowed to contradict a decision another had already made.
Parallel agents don't scale past the human in the middle. You run five to go faster, four of them are right, the product is broken, and the only thing that catches it is you — reading everything, holding the whole picture, re-explaining choices that were already settled.
That isn't a prompting problem. Your agents have memory and they have verification, and neither answers the question that actually breaks a parallel run:
Did these two agents just settle the same question differently?
Concord Engine answers it by comparison, never by a model, and refuses the second answer at the moment it is written.
Recorded, not drawn. brag/record.mjs runs the real CLI and captures its output verbatim; brag/video.html only renders what was captured. The loop shows the refusal arc — the full run also writes the contract, binds it and briefs four workers first.
This is the part that gets undersold. A "decision" is not a variable name. It is any question two agents could answer differently and both be reasonable — and the cost is never the question itself, it's that nothing goes red.
| Kind | Real examples | ||||
|---|---|---|---|---|---|
convention | money is integer minor units, never a float · timestamps are UTC ISO-8601 strings · pagination is cursor-based · every non-2xx body is {"error":" "} · retries are idempotent and capped at 3 · migrations ship in two reversible stages | ||||
api-contract | POST /api/orders returns 201, not 200 · tenant scoping lives in the path, not a header | ||||
enum | order status is `pending\ | paid\ | shipped · roles are owner\ | admin\ | member` · webhook events are a closed set |
schema | id is a uuid and not null · amount_cents is an integer · soft deletes use deleted_at, not a boolean | ||||
naming | the identifier is user_id · the destination field is url, not target |
Four agents implementing four reasonable answers to "what does an error body look like" produce four green test suites and one broken product. That is the whole category, and it is much wider than route paths.
A refunds feature, split across a backend worker and a client worker. The backend settles the error shape. The client, working in parallel and with no visibility into the backend's files, reaches a different answer:
$ concord-engine decide --unit client --kind convention \
--subject "error response body shape" \ --value 'every non-2xx body is {"code":" ","detail":" "}' --as client
refused this contradicts a decision already in force. d-003 api (lead): error response body shape = every non-2xx body is {"error":" "} because: the client shows it to a person yours: every non-2xx body is {"code":" ","detail":" "}
Adopt the existing value, or supersede it deliberately: --supersedes d-003 --layer pm (an override, recorded as one) --force (record the disagreement for check to surface)
Verbatim from the recording above.
The agent is stopped at the moment it tries to disagree, and told what is in force, who decided it, why, and the two legitimate ways out. Not at integration. Not by you.
As a skill, which is how most people will use it. Describe the task; the agent runs the whole loop — authors the contract, binds it, briefs each worker, fans out, gates every decision, runs the acceptance checks, writes the design doc.
/concord-engine:concord-engine add refunds across the API, the client and the schema
/concord-engine:concord-engine migrate us off the legacy auth tables, five workers /concord-engine:concord-engine rename the tenant concept to workspace everywhere
Nothing about the task has to be small, and nothing has to be a route.
As an MCP server, so an agent already mid-task can reach the gate without being handed a workflow. Twelve tools: write_contract, bind_contract, brief_unit, fleet_plan, run_acceptance, generate_docs, cost_report, plus record_decision, binding_decisions, open_conflicts, record_attempt, status.
As a CLI, for humans and for CI. concord-engine check exits non-zero when anything contradicts, which is a one-line pipeline step.
| Tool | Answers | Doesn't answer |
|---|---|---|
| Handoff / memory tools | "what did the last agent know?" | "do these two agree?" |
| Orchestrator verification | "did this worker do its task?" | "do these two agree?" |
| Edit-conflict detection | "did two agents touch one file?" | "do these two agree?" |
And the obvious way to answer it — store decisions as prose, ask a model whether two of them conflict — is slow, costs a call per check, and is wrong often enough that people stop trusting it. A coordination layer nobody trusts is worse than none, because it adds latency and false alarms to a workflow that had neither.
Concord Engine decides agreement by comparison, never by a model. Decisions are typed and narrow, so a contradiction is a comparison: same subject, different value. No API call exists anywhere in the decision path — there's a test that fails if any file in that path can reach outside the process, and a second one that fails if any file in the package, anywhere, calls a model.
The gate above is one organ. v0.2 is the body around it: you describe a task, and the fleet that builds it is bound to one set of decisions from before the first line of code.
describe a task
| [1] CONTRACT the agent authors JSON to a published schema; | the package validates it and stores it v [2] BIND the contract's decisions enter the log at PM layer, | binding before any code exists v [3] BRIEF one brief per unit: its slice, the decisions it must | honour, what it may not decide, how it will be judged v [4] FAN OUT the host spawns one worker per unit, each getting a | brief and nothing else v [5] GATE a worker that tries to decide something contradictory | is refused, told what is in force and who may override v [6] ACCEPT every acceptance criterion carries a command; the run | is not done until all of them exit 0 v [7] DOCS the design doc is generated from the decision log — | what was decided, by whom, and why v [8] COST what the fan-out sent, in bytes
concord-engine spec --schema # the contract shape, as JSON Schema
concord-engine spec --from contract.json # validate and store it concord-engine bind --contract add-refunds concord-engine fleet --contract add-refunds # every brief, as JSON concord-engine brief --contract add-refunds api # one worker's brief concord-engine accept --contract add-refunds # run every check concord-engine docs --contract add-refunds concord-engine cost --contract add-refunds
Every loop command takes --contract. The MCP server exposes the same set as write_contract, bind_contract, brief_unit, fleet_plan, run_acceptance, generate_docs and cost_report.
One JSON document. The agent writes it; the package decides whether it holds.
openSubjects is the part people skip and shouldn't. Naming a thing before anyone decides it is what stops two workers inventing two different names for it — see Honest limits for the run where that went wrong.
{
"id": "add-refunds", "goal": "one sentence a reviewer can judge the result against", "scope": { "in": ["..."], "out": ["..."] }, "decisions": [ // binding from t=0, at PM layer { "kind": "api-contract", "subject": "refund endpoint", "value": { "method": "POST", "path": "/api/refunds", "status": 201 }, "rationale": "why this and not the alternative" } ], "openSubjects": [ // known to need deciding, not yet decided { "kind": "convention", "subject": "error response body shape", "note": "the server and the client both serialise this" } ], "units": [ // one worker each { "id": "api", "goal": "...", "files": ["src/api/**"], "mayDecide": ["convention"], // everything else must be requested "dependsOn": [] } ], "acceptance": [ { "id": "a1", "statement": "refunds endpoint returns 201", "check": "npm test -- refunds", "unit": "api" } ] }
Validation is not a formality. A contract is rejected when two of its own decisions contradict each other, when a unit depends on one that doesn't exist, when the dependency graph has a cycle, when a unit has no acceptance criterion, or when a criterion has no command. All of it in one pass, because fixing one error per round trip is the expensive way to find four:
$ concord-engine spec --from contract.json
concord-engine: contract is not valid:
bind then puts the contract's decisions into the log at PM layer. If one of them contradicts a decision already live, binding refuses — a new contract quietly overriding decisions in force is the exact failure this tool exists to prevent.
A brief, and not the conversation. This is the actual brief the unit that wrote this file was given. Verbatim, abridged only where marked:
$ concord-engine brief --contract concord-engine-v2 readme
You are one worker on "concord-engine-v2". Your unit is "readme".
GOAL Rewrite README.md around the loop without losing the v0.1 pitch that the gate is the product.
FILES YOU OWN README.md Do not edit files outside this list. Another worker owns them.
DECISIONS ALREADY IN FORCE — these are not suggestions
WHAT YOU MAY DECIDE nothing — you write code and decide nothing
WHAT YOU MUST NOT DECIDE ALONE naming, convention, api-contract, enum, schema
RECORD A DECISION LIKE THIS — the flags are what enforce the two lists above concord-engine decide --contract concord-engine-v2 --unit readme \ --kind --subject " " --value ' ' --as readme --rationale " "
Omitting --unit skips the check on what you may decide. Use the MCP tool record_decision if you have it; it gates the same way. A refusal means a decision already covers this: adopt the existing value. Do not work around it, and do not --force it.
DONE MEANS [a-readme] the README covers the loop and keeps the gate pitch $ test -f README.md && grep -q 'spec --schema' README.md && grep -q 'refus' README.md && grep -q -i 'estimate' README.md
fleet prints all of them at once,
Only the beginning is shown; read the rest in the repo