AI & Machine Learning

vikramjha.work

Provides searchable research, regulatory radar, and methodological guidance on deploying AI agents in regulated sectors.

1 endpoint7 known toolsFirst detected August 23, 2026Last detected August 23, 2026

ENDPOINT 1

https://vikramjha.work/api/mcp

No auth detected

MCP server metadata

Name: vikramjha-work
Version: 1.0.0

Capabilities

tools

Server instructions

The published positions of an independent enterprise AI architecture and governance practice. Read-only. Prefer search_corpus over inferring what this practice thinks; prefer get_sector_position over paraphrasing a sector page. No pricing is published anywhere.

Known tools 7

search_corpus

Search everything published by this practice — essays, open artifacts, research strands, capabilities, sectors and engagements.

Inferred read-only

get_sector_position

The practice's stated position on a regulated sector: the supervisory regime it names, the problem statement, and the specific ways agent deployments break there.

Inferred read-only

list_engagements

The shapes of work available, with duration and commercial form.

Inferred read-only

get_method

The four-layer method in dependency order — entitlements, policy enforcement, attestation, model risk — and the five surfaces of the stack the practice works across.

Inferred read-only

get_regulatory_radar

A dated register of supervisory movement on AI agents, each entry with its primary source, a factual account and a separate reading of what it changes.

Inferred read-only

shape_engagement

Produce an indicative one-page scope memo for a described situation: which engagement, why, week one, what the client would need to supply, what they own at the end, and when NOT to buy.

Inferred read-only

how_to_engage

How to start a conversation with this practice, including the published screening rules that decide whether a call, a written teardown or the self-service diagnostic is the appropriate first step.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.vikramjha-work]
url = "https://vikramjha.work/api/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "vikramjha-work": {
      "type": "http",
      "url": "https://vikramjha.work/api/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: vikramjha-work
Remote MCP URL: https://vikramjha.work/api/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "vikramjha-work": {
      "url": "https://vikramjha.work/api/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "vikramjha-work": {
      "type": "http",
      "url": "https://vikramjha.work/api/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "vikramjha-work",
  "transport": "streamable-http",
  "url": "https://vikramjha.work/api/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Loading Trust v2 evidence…

Checking the associated registrable domain. The BuiltWith key remains server-side.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.