Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Repository MCP adapter for company-scoped workflow candidates and conditional API discovery.
These three are never merged into one score: opinions, measurements and popularity are different things.
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.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"agenticorg": {
"command": "npx",
"args": [
"-y",
"agenticorg-mcp-server"
]
}
}
}Run this in your terminal
claude mcp add agenticorg -- npx -y agenticorg-mcp-serverPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agenticorg": {
"command": "npx",
"args": [
"-y",
"agenticorg-mcp-server"
]
}
}
}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": {
"agenticorg": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"agenticorg-mcp-server"
]
}
}
}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.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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These 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 mishrasanjeev, 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.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
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 (5.0.0) reached the registry 28 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: Spec Driven Development, Remote Desktop Commander, Python MCP
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Local-only Python MCP server for the Files.com API.
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.
AgenticOrg is an enterprise AI agent platform for building, running, and governing agent workflows across finance, HR, marketing, operations, back office, communications, and bounded agentic-commerce use cases. The platform is source-available under the Orchestrum Personal Use License 1.0: only individuals' personal use is free, and any organisation needs a signed agreement with Orchestrum Technologies LLP; the SDKs and MCP server are Apache-2.0 open source (see Licence).
Ownership: AgenticOrg is owned by Orchestrum Technologies LLP.
Inventor / Owner: Sanjeev Kumar
Contact: sanjeev@orchestrum.in | mishra.sanjeev@gmail.com
Website demo and trial lead notifications default to sanjeev@orchestrum.in. Self-hosted operators can select their own single marketing inbox with AGENTICORG_DEMO_NOTIFY_TO. This does not redirect requester confirmations, workspace notifications, or account-recovery email, and does not replace SMTP setup.
See the canonical ownership and contact statement and NOTICE.
Website | Application | Playground | User manual | Technical documentation | Current product status | Security policy
Start with a measurable pilot: bank service cases, fintech/API integrations, or merchant and external-buyer workflows. The visual rollout checklist explains source setup, review, external confirmation and expansion. Discuss your task and systems at sanjeev@orchestrum.in; do not send credentials or customer data in a public enquiry.
The AgenticOrg platform is source-available under the [Orchestrum Personal Use License 1.0](LICENSE). Only an individual using it for their own personal purposes is free. Every organisation (companies, firms, sole proprietors' businesses, charities, schools, universities, research bodies and government) needs prior written permission in a signed agreement with Orchestrum Technologies LLP, for any use: evaluation, testing, pilots, internal use, hosting, resale or embedding, paid or free.
The AgenticOrg SDKs (`sdk/`, `sdk-ts/`) and the MCP server (`mcp-server/`) are open source under the Apache License 2.0, free for any use including commercial.
| Directory | Licence |
|---|---|
sdk/ (Python SDK) | Apache License 2.0: open source, free for any use including commercial |
sdk-ts/ (TypeScript SDK) | Apache License 2.0: open source, free for any use including commercial |
mcp-server/ (MCP server) | Apache License 2.0: open source, free for any use including commercial |
tests/fixtures/ucp/, core/commerce/acp/schemas/ (vendored protocol schemas) | Apache License 2.0 (third-party, unchanged) |
Everything else: the AgenticOrg platform (api/, core/, auth/, connectors/, ui/ and the website, workers, docs/, scripts/, migrations/, tests) | Orchestrum Personal Use License 1.0: individuals' personal use only; any organisation needs a signed agreement with Orchestrum Technologies LLP |
Live product totals and the deployed product version are published by the public product facts endpoint:
GET https://app.agenticorg.ai/api/v1/product-facts
The response contains version, agent_count, connector_count, and tool_count. Do not copy those values into documentation, page copy, or tests: they are computed from runtime registries and can change independently of a documentation release. The version declared for source builds is in pyproject.toml.
Billing limits and list prices come from core/billing/catalog.py. Production deployment behavior comes from scripts/deploy_cloud_run.sh.
New agents default to gemini-3.5-flash-lite; explicitly selected models remain unchanged. Save your Google or other provider key in the protected AI credential settings. Model selection, fallback and company scope remain configurable. For this model, Agent Configuration > Gemini thinking offers an optional medium profile for multi-step reasoning. Existing agents and generic calls keep the provider default; no global flag or default is changed. The API equivalent is llm.thinking_level="medium"; set it to null to restore the provider default. Both runtime clients honor explicit profiles. Thinking is billed as output tokens; budget for its additional token use and response time within existing limits. It is not a correctness guarantee. Older model settings and all feature flags remain unchanged. See reasoning acceptance.
The Channels dashboard connects your own WhatsApp Cloud API, Meta Messenger, Telegram, Viber, inbound Mailgun email or signed gateway to an agent or workflow. Credentials are encrypted, callbacks are authenticated, unlinked messages require review, and private sender links delegate only your current permissions. Existing Twilio voice/call setup and remote MCP tool discovery remain separate integrations. Native channel replies default to optional status notices. Telegram agent connections can opt into bounded final-answer replies for the linked private sender under Channels > Reply content. Traces and tool-call records stay in AgenticOrg; approvals, sender authorization and tenant controls still apply. The encrypted intake carries the authenticated sender identity across services; older receipts without that proof remain withheld, even if the agent completed. For tool-free Telegram agents without traffic splits in this opt-in mode, follow-ups may use up to four recent, confirmed question/answer pairs from the same linked private sender and agent/company scope, within 30 minutes. This is bounded text context, not durable memory or permission to repeat actions. Hindi and other Unicode model input remains readable before privacy scanning; existing redaction still applies. With AGENTICORG_PII_HINDI_GRAMMAR_ENABLED=true (default off), targeted Hindi grammar checks distinguish referential name/colour questions from named values. This is not a general-purpose Hindi entity-recognition model; quoted names, unknown words and structured identifiers retain privacy scanning.
Follow the channel account and workflow guide for account creation, callback registration, sender linking and verification. Local wire-contract tests are not proof of real provider-account delivery. Reuse an existing Telegram connection for an already connected bot; a second connection must not overwrite its webhook. Change its destination through Save settings only when authorized and no tasks are queued or running. Verify real model reasoning separately from transport-only workflows, and do not claim a combined Telegram-to-Gemini flow unless one delivery proves both.
Acceptance checks validate the actual answer as well as the terminal status. A completed, high-confidence model run can still be wrong; compare numeric results independently and preserve PII protections while diagnosing it. See the bounded production acceptance runbook.
The production platform currently includes governed agent/workflow execution, document ingestion with scanned-document OCR, signed Twilio voice with provider-managed STT/TTS, tenant-scoped browser RPA, Python and TypeScript SDKs, MCP/A2A surfaces, and the bounded Shopify-to-OACP commerce runtime. See the current product status for the exact shipped, configuration-dependent, and not-shipped boundaries.
External actions remain explicit. A voice provider, connector, browser script, buyer channel, payment rail, merchant system, or POS path is usable only when the target tenant has the required credentials, scopes, configuration, and provider approval.
The repository includes a tenant-gated business onboarding case workflow with read-only provider investigation, a cited memo, deterministic policy scoring, screening dispositions, human review, and an auditable hand-off. Provider calls are refused unless the active role agent, registered tools, exact local case purpose, and delegated grant all authorize the call. This case-specific check is strict even if general tool enforcement is in off or warn mode.
AgenticOrg pins grantex==0.7.1 and calls its enforcement check with the grant token, connector, tool and any numeric amount. It does not pass a case id or case purpose, so a token's case purpose and per-case caps are not checked on this path. The role's case_purposes list is a local AgenticOrg control, and pooled grants are not bound to one case. Decision and analyst actions still require a signed-in human; API keys, agent tokens, and MCP tools cannot act as that human. The case runtime is off for a tenant until enabled and configured. This source description is not a claim that a particular hosted deployment has enabled the workflow. See the case lifecycle and setup, grant-enforcement runbook, and decision requests.
Voice, email, OCR, and browser RPA can be exercised together before release with the Docker-backed local multichannel simulation. It uses fresh PostgreSQL, local Mailpit delivery, real Tesseract, and optional real Playwright Chromium while keeping paid calls and production mutations off.
Knowledge upload status distinguishes extraction from searchable indexing. With opt-in upload recovery, transient native embedding failures retry on the existing worker; the previous searchable copy remains until replacement succeeds. Malformed PDF/Office files are refused before replacement. See Knowledge and OCR for status meanings, citations and recovery limits. For a reasoning-only agent, disable suggested tools and leave tool/connector selection empty; this does not bypass tenant budgets. Provider charges and quotas still apply. Use structured output for conf
Only the beginning is shown; read the rest in the repo