Skip to main content
Glama
RudrenduPaul

teamspend

by RudrenduPaul
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Related Servers

Alternatives to teamspend

No user-submitted related servers found.

    Related Servers

    • LLM Usage & Cost Tracker

      zhaoyue722
      A
      license
      A
      quality
      A
      maintenance
      A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.
      7
      23 PyPI
      4
      MIT

    • Cost Management MCP

      knishioka
      A
      license
      B
      quality
      C
      maintenance
      An MCP server for unified cost tracking and analysis across AWS, OpenAI, and Anthropic. It enables users to query expenditures, compare costs across providers, and analyze usage trends through natural language.
      10
      MIT

    • token-meter

      whdrnr2583-cmd
      A
      license
      A
      quality
      A
      maintenance
      Local-first dashboard + MCP server that parses Claude Code and Codex JSONL files into a SQLite cost / token tracker. Per-MCP and per-tool breakdown, session drill-down, dedup by request_id; never talks to vendor APIs
      5
      79 npm
      1
      MIT

    • Tallybook

      magna-nz
      A
      license
      A
      quality
      A
      maintenance
      Prices your Claude Code and Codex sessions from the transcripts on disk, shows what each agent cost over any period, and tells you in plain English what would have been cheaper. CLI, Browser UI and MCP server.
      8
      5
      MIT

    • openai-usage-mcp

      dlaporte
      A
      license
      A
      quality
      D
      maintenance
      MCP server for querying OpenAI usage and cost data, including spend summaries, daily breakdowns, month-over-month comparisons, and token usage by model.
      3
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.6/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only a single tool, there is no possibility of confusing it with another. The tool's description clearly limits its purpose to a specific before/after cost comparison, so an agent cannot misselect it for anything else.

    Naming Consistency4/5

    There is only one tool named 'run', so there is no inconsistency in naming conventions. However, the name is very generic and does not convey the tool's specific function, which is a minor weakness since a descriptive name would be more helpful.

    Tool Count3/5

    The server exposes only one tool, which is below the typical 3-15 range. While the tool is substantial and covers a focused use case, the single-tool surface feels thin for a server, though it is not an extreme mismatch because the tool is not trivial.

    Completeness4/5

    Within its declared scope of comparing AI-coding-tool spend between two windows, the tool provides a complete workflow including error handling for missing credentials and a report file. Minor gaps like lacking multi-tool comparison or raw spend analytics don't affect its stated purpose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources