diff --git a/recipes/cvxcanon/meta.yaml b/recipes/cvxcanon/meta.yaml
new file mode 100644
index 0000000000000..af921c67e2bda
--- /dev/null
+++ b/recipes/cvxcanon/meta.yaml
@@ -0,0 +1,54 @@
+{% set name = "CVXcanon" %}
+{% set version = "0.1.1" %}
+{% set sha256 = "70d7ca2e9200e2eb5d2d74131249110d8582c4227c92e553891e73c53c630fc5" %}
+
+package:
+  name: {{ name|lower }}
+  version: {{ version }}
+
+source:
+  fn: {{ name }}-{{ version }}.tar.gz
+  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
+  sha256: {{ sha256 }}
+
+build:
+  number: 0
+  script: python setup.py install --single-version-externally-managed --record record.txt
+
+requirements:
+  build:
+    - python
+    - setuptools
+    - numpy x.x
+    - scipy
+    - gcc  # [not win]
+
+  run:
+    - python
+    - numpy x.x
+    - scipy
+
+test:
+  # Python imports
+  imports:
+    - canonInterface
+    - CVXcanon
+
+about:
+  home: https://github.com/cvxgrp/CVXcanon
+  license: Apache License 2.0
+  summary: |
+    A low-level library to perform the matrix building step in cvxpy,
+    a convex optimization modeling software.
+  description: |
+    Convex optimization modeling tools like CVX, CVXPY, and Convex.Jl translate
+    high-level problem descriptions into low-level, canonical forms that are
+    then passed to an backend solver. CVXcanon is a software package that factors
+    out the common operations that all such modeling systems perform into a single
+    library with a simple C++ interface. CVXcanon removes the need to reimplement
+    this canonicalization process in new languages and provides significant
+    performance gains over high level language implemententations.
+
+extra:
+  recipe-maintainers:
+    - sebp
diff --git a/recipes/cvxpy/meta.yaml b/recipes/cvxpy/meta.yaml
new file mode 100644
index 0000000000000..b18781189e375
--- /dev/null
+++ b/recipes/cvxpy/meta.yaml
@@ -0,0 +1,78 @@
+{% set name = "cvxpy" %}
+{% set version = "0.4.10" %}
+{% set sha256 = "3f5112bd42855943298cf2d85d2a42832e7ebdaf55e053a9e3d2db52a46f001b" %}
+
+package:
+  name: {{ name|lower }}
+  version: {{ version }}
+
+source:
+  fn: {{ name }}-{{ version }}.tar.gz
+  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
+sha256: {{ sha256 }}
+
+build:
+  number: 0
+  script: python setup.py install --single-version-externally-managed --record record.txt
+
+requirements:
+  build:
+    - python
+    - setuptools
+    - ecos >=2
+    - scs >=1.1.3
+    - multiprocess
+    - fastcache
+    - six
+    - toolz
+    - numpy >=1.9
+    - scipy >=0.15
+    - cvxcanon >=0.0.22
+
+  run:
+    - python
+    - ecos >=2
+    - scs >=1.1.3
+    - multiprocess
+    - fastcache
+    - six
+    - toolz
+    - numpy >=1.9
+    - scipy >=0.15
+    - cvxcanon >=0.0.22
+
+test:
+  # Python imports
+  imports:
+    - cvxpy
+    - cvxpy.atoms
+    - cvxpy.atoms.affine
+    - cvxpy.atoms.elementwise
+    - cvxpy.constraints
+    - cvxpy.expressions
+    - cvxpy.expressions.constants
+    - cvxpy.expressions.variables
+    - cvxpy.interface
+    - cvxpy.interface.numpy_interface
+    - cvxpy.lin_ops
+    - cvxpy.problems
+    - cvxpy.problems.problem_data
+    - cvxpy.problems.solvers
+    - cvxpy.tests
+    - cvxpy.transforms
+    - cvxpy.utilities
+
+about:
+  home: http://github.com/cvxgrp/cvxpy/
+  license: Apache License 2.0
+  summary: 'A domain-specific language for modeling convex optimization problems in Python.'
+  description: |
+    CVXPY is a Python-embedded modeling language for convex optimization problems.
+    It allows you to express your problem in a natural way that follows the math,
+    rather than in the restrictive standard form required by solvers.
+  doc_url: http://www.cvxpy.org/
+  dev_url: https://github.com/cvxgrp/cvxpy
+
+extra:
+  recipe-maintainers:
+    - sebp
diff --git a/recipes/scs/blas_mkl.patch b/recipes/scs/blas_mkl.patch
new file mode 100644
index 0000000000000..78de5b6b05f7f
--- /dev/null
+++ b/recipes/scs/blas_mkl.patch
@@ -0,0 +1,13 @@
+--- setup.py.orig	2016-09-25 20:32:57.885171517 +0100
++++ setup.py	2016-09-25 20:33:06.368134063 +0100
+@@ -52,10 +52,6 @@
+ 
+     # environment variables not set, using defaults instead
+     blas_info = get_info('blas_opt')
+-    # ugly hack due to scipy bug
+-    if 'libraries' in blas_info:
+-        if 'mkl_intel_lp64' in blas_info['libraries']:
+-            blas_info = get_info('blas')
+     if not blas_info:
+         blas_info = get_info('blas')
+     print(blas_info)
diff --git a/recipes/scs/meta.yaml b/recipes/scs/meta.yaml
new file mode 100644
index 0000000000000..a0029471fc5b8
--- /dev/null
+++ b/recipes/scs/meta.yaml
@@ -0,0 +1,54 @@
+{% set name = "scs" %}
+{% set version = "1.2.6" %}
+{% set sha256 = "2a00f7c594838aea045540c222774fa0e826b6663832671e58434acf89cb56ff" %}
+
+package:
+  name: {{ name|lower }}
+  version: {{ version }}
+
+source:
+  fn: {{ name }}-{{ version }}.tar.gz
+  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
+  sha256: {{ sha256 }}
+  patches:
+   # List any patch files here
+   - blas_mkl.patch
+
+build:
+  number: 0
+  script: python setup.py install --single-version-externally-managed --record record.txt
+
+requirements:
+  build:
+    - python
+    - setuptools
+    - numpy x.x
+    - scipy >=0.13.2
+    - gcc  # [not win]
+
+  run:
+    - python
+    - numpy x.x
+    - scipy >=0.13.2
+
+test:
+  # Python imports
+  imports:
+    - scs
+
+about:
+  home: http://github.com/cvxgrp/scs
+  license: MIT
+  summary: 'scs: splitting conic solver'
+  description: |
+    SCS (splitting conic solver) is a numerical optimization package for solving
+    large-scale convex cone problems, based on our paper Conic Optimization via
+    Operator Splitting and Homogeneous Self-Dual Embedding. It is written in C
+    and can be used in other C, C++, Python, Matlab, R, Julia, Java, and Scala
+    programs via included interfaces (Julia interface available here). It can
+    also be called as a solver from convex optimization toolboxes CVX (3.0 or
+    later), CVXPY, Convex.jl, and Yalmip.
+
+extra:
+  recipe-maintainers:
+    - sebp